Testing Your Neural Net

Here's a simple dataset that you can use to test your neural net:

% This dataset contains a 7x7 grid of pixel values that form
% an image of the letter 'Y':
%
% 1000001
% 1100011
% 1110111
% 0111110
% 0011100
% 0011100
% 0011100
%
@RELATION Y

@ATTRIBUTE x continuous
@ATTRIBUTE y continuous
@ATTRIBUTE g continuous

@DATA
0,-0.7,1
0.2333,-0.7,1
0.4667,0.7,0
0.7,0,0
0,0.4667,0
0.2333,0.4667,0
-0.4667,-0.4667,0
-0.2333,0,1
0.7,0.2333,1
-0.7,0.4667,1
-0.2333,0.4667,0
0.4667,-0.7,0
0.7,-0.7,0
-0.7,-0.2333,0
0.7,-0.2333,0
-0.7,0.7,1
-0.4667,0.4667,1
0.7,-0.4667,0
0.4667,0.4667,1
-0.2333,0.2333,1
0,0.2333,0
-0.7,-0.7,0
0.2333,-0.2333,1
0.4667,-0.2333,0
0.2333,-0.4667,1
-0.4667,0,1
0.4667,-0.4667,0
0.2333,0.2333,1
-0.4667,0.7,0
0.2333,0,1
0.4667,0,1
-0.4667,-0.2333,0
-0.7,0,0
0,0,1
-0.4667,-0.7,0
-0.2333,-0.7,1
-0.2333,0.7,0
0,0.7,0
0.7,0.4667,1
-0.2333,-0.2333,1
0.7,0.7,1
-0.7,0.2333,1
-0.7,-0.4667,0
-0.4667,0.2333,1
0.2333,0.7,0
-0.2333,-0.4667,1
0,-0.4667,1
0.4667,0.2333,1
0,-0.2333,1

I created a neural net with one hidden layer of three nodes to learn this data. My network has 13 weights. Here's a visual diagram of my network layout:



In order to reproduce these results, you will need to use the same parameters (including initial weights) that I used. I used a learning rate of 0.175, and a momentum term of 0.9. The previous delta for each weight is initialized to 0. Below is a detailed log spew for the first three epochs. Typically you will want to shuffle the dataset before each epoch, but in order to make reproduceable results I just present them in the order in which they appear in the ARFF file. (If you want to produce exactly equivalent output so you can diff your results with mine, I use printf("%.14lg", value); to print doubles.) The text in red was done by hand, and shows how these values are computed.

My code was designed to follow Table 4.2 on page 98 of Machine Learning so if you encounter something that is unclear, that table should settle the matter. Don't get confused because the notation below uses "e" instead of lowercase delta to represent error, "d" instead of capital delta to represent the change in weight, and I subscript my weights differently than table 4.2 does. Sorry, it didn't occur to me to use the same notation until after I already did the work. If this really bothers you, feel free to standardize it and send me a copy.

Initial Weights:
w_0=0.02, w_1=-0.01, w_2=0.03, w_3=0.02, w_4=-0.01, w_5=-0.03, w_6=0.03, w_7=0.01, w_8=0.04, w_9=-0.02, w_10=-0.02, w_11=0.03, w_12=0.02

---Epoch 1---
Pattern: {0, -0.7, 1}
Forward propagating...
o_1 = squash(w_4*1+w_5*x+w_6*y) = 1/(1+exp(-(-.01*1-.03*0+.03*(-.7))))
o_2 = squash(w_7*1+w_8*x+w_9*y) = 1/(1+exp(-(.01*1+.04*0-.02*(-.7))))
o_3 = squash(w_10*1+w_11*x+w_12*y) = 1/(1+exp(-(-.02*1+.03*0+.02*(-.7))))
o_0 = squash(w_0*1+w_1*o_1+w_2*o_2+w_3*o_3) = 1/(1+exp(-(.02*1-.01*.4922506205862+.03*.50599971201659+.02*.49150081873869)))
o_0=0.51002053349535, o_1=0.4922506205862, o_2=0.50599971201659, o_3=0.49150081873869
Back propagating...
e_0 = output*(1-output)*(target-output) = .51002053349535*(1-.51002053349535)*(1-.51002053349535)
e_1 = o_1*(1-o_1)*(w_1*e_0) = .4922506205862*(1-.4922506205862)*(-.01*.1224456672531)
Note that the term "(w_1*e_0)" is a sum over all the outputs of n_1. It just happens that in this example, n_1 has only one output.
e_2 = o_2*(1-o_2)*(w_2*e_0)
e_3 = o_3*(1-o_3)*(w_3*e_0)
e_0=0.1224456672531, e_1=-0.00030604063598154, e_2=0.00091821027577176, e_3=0.00061205143636003
Descending Gradient...
d_0 = (d_0*momentum)+(learning_rate*e_0*1) = 0*.9+.175*.1224456672531*1
w_0 = w_0 + d_0 = .02+.0214279917693
d_1 = (d_1*momentum)+(learning_rate*e_0*o_1) = 0*.9+.175*.1224456672531*.4922506205862
w_1 = w_1 + d_1 = -.01+.0105479422563
etc.
w_0=0.041427991769293, w_1=0.00054794224635029, w_2=0.040842557664356, w_3=0.030531875498533, w_4=-0.010053557111297, w_5=-0.03, w_6=0.030037489977908, w_7=0.01016068679826, w_8=0.04, w_9=-0.020112480758782, w_10=-0.019892890998637, w_11=0.03, w_12=0.019925023699046
Pattern: {0.2333, -0.7, 1}
Forward propagating...
o_0=0.51937076254275, o_1=0.49048145010241, o_2=0.50839206766384, o_3=0.49329005095298
Back propagating...
e_0=0.11997696456587, e_1=1.6429155600529e-05, e_2=0.0012246964204031, e_3=0.00091561550994929
Descending Gradient...
w_0=0.081709153160683, w_1=0.020339223490917, w_2=0.061275043552619, w_3=0.050367665965892, w_4=-0.010098883409234, w_5=-0.02999932923865, w_6=0.030069218386464, w_7=0.010519626790265, w_8=0.040050001293104, w_9=-0.020363738753185, w_10=-0.019636260183169, w_11=0.030037382292232, w_12=0.019745382128218
Pattern: {0.4667, 0.7, 0}
Forward propagating...
o_0=0.53693684122531, o_1=0.49923722121815, o_2=0.5037390166178, o_3=0.50205097690221
Back propagating...
e_0=-0.13350165113703, e_1=-0.00067882839986206, e_2=-0.0020449655090692, e_3=-0.0016810133573426
Descending Gradient...
w_0=0.094599409463954, w_1=0.026487802776232, w_2=0.067895532521447, w_3=0.056490566371519, w_4=-0.010258472047353, w_5=-0.030054167165922, w_6=0.030014617475181, w_7=0.010484803818982, w_8=0.039927985011358, w_9=-0.020840379223009, w_10=-0.019699469786783, w_11=0.029933733791814, w_12=0.019377780578199
Pattern: {0.7, 0, 0}
Forward propagating...
o_0=0.5425218275149, o_1=0.49217654129003, o_2=0.5096074156859, o_3=0.50031353592578
Back propagating...
e_0=-0.13464952000752, e_1=-0.00089142418518388, e_2=-0.0022846813779855, e_3=-0.0019016061639713
Descending Gradient...
w_0=0.082636974135581, w_1=0.020424040500374, w_2=0.061845753658376, w_3=0.050211955680091, w_4=-0.010558101054067, w_5=-0.030212720763152, w_6=0.029965476655026, w_7=0.01005364390368, w_8=0.039538296888984, w_9=-0.021269355645851, w_10=-0.020089139508731, w_11=0.029607503386351, w_12=0.019046939183182
Pattern: {0, 0.4667, 0}
Forward propagating...
o_0=0.53712075340526, o_1=0.50085669588687, o_2=0.5000318089059, o_3=0.49720004602046
Back propagating...
e_0=-0.1335400626301, e_1=-0.00068185491015982, e_2=-0.0020647214458799, e_3=-0.0016762743586904
Descending Gradient...
w_0=0.048501271379779, w_1=0.0032618784080513, w_2=0.044715453842903, w_3=0.032941884132886, w_4=-0.010947091769388, w_5=-0.03035541900066, w_6=0.029865561121737, w_7=0.0093042737268786, w_8=0.039187577578847, w_9=-0.021824065388697, w_10=-0.020733190271254, w_11=0.029313896021434, w_12=0.018612276410106
Pattern: {0.2333, 0.4667, 0}
Forward propagating...
o_0=0.52223707311451, o_1=0.49897731301448, o_2=0.50206534931787, o_3=0.4986980257105
Back propagating...
e_0=-0.13030102861535, e_1=-0.00010625608341682, e_2=-0.0014565925538992, e_3=-0.0010730830706198
Descending Gradient...
w_0=-0.0050235411081283, w_1=-0.023562087474804, w_2=0.017849748505535, w_3=0.00602716823966, w_4=-0.011315778227775, w_5=-0.030488185584662, w_6=0.029766958941804, w_7=0.0083749368708255, w_8=0.038812461167229, w_9=-0.022442267712616, w_10=-0.021500625494884, w_11=0.029005838093944, w_12=0.018133438537253
Pattern: {-0.4667, -0.4667, 0}
Forward propagating...
o_0=0.49878407485227, o_1=0.49725523213331, o_2=0.50018374188812, o_3=0.48912658311464
Back propagating...
e_0=-0.1246952812738, e_1=0.00073449814649656, e_2=-0.00055644477749636, e_3=-0.00018780100196183
Descending Gradient...
w_0=-0.07501754657016, w_1=-0.058554598450626, w_2=-0.017244232965176, w_3=-0.028869637014739, w_4=-0.011519058864686, w_5=-0.030667663810134, w_6=0.029618228679995, w_7=0.0074411558643157, w_8=0.038520302632863, w_9=-0.022953203568054, w_10=-0.022224182371494, w_11=0.028743924136535, w_12=0.017717822629018
Pattern: {-0.2333, 0, 1}
Forward propagating...
o_0=0.46827456776882, o_1=0.49890892850736, o_2=0.49961359239194, o_3=0.49276796943063
Back propagating...
e_0=0.13239617478836, e_1=-0.0019380919840332, e_2=-0.00057076727954998, e_3=-0.00095535746580487
Descending Gradient...
w_0=-0.11484282089803, w_1=-0.078488472430993, w_2=-0.037253103800449, w_3=-0.0488596577568, w_4=-0.012041177535112, w_5=-0.03075006676258, w_6=0.029484371444366, w_7=0.0065008686845357, w_8=0.03828066295304, w_9=-0.023413045837948, w_10=-0.023042571116959, w_11=0.028547206431802, w_12=0.017343768311606
Pattern: {0.7, 0.2333, 1}
Forward propagating...
o_0=0.4509356316181, o_1=0.49332851585835, o_2=0.50695831802499, o_3=0.50024669361308
Back propagating...
e_0=0.13594432271833, e_1=-0.0026670406458514, e_2=-0.0012658417847663, e_3=-0.0016605478662706
Descending Gradient...
w_0=-0.1268953113174, w_1=-0.084692547094272, w_2=-0.043200419143886, w_3=-0.054949679282475, w_4=-0.01297781645152, w_5=-0.031150941898899, w_6=0.029255011330332, w_7=0.0054330879103997, w_8=0.037909921622565, w_9=-0.02387858503632, w_10=-0.024069716864474, w_11=0.028166743383924, w_12=0.016939323407925
Pattern: {-0.7, 0.4667, 1}
Forward propagating...
o_0=0.44572679903399, o_1=0.50562005246938, o_2=0.49193870037342, o_3=0.49103074850759
Back propagating...
e_0=0.13693564399603, e_1=-0.0028989908148449, e_2=-0.0014785348764599, e_3=-0.0018805370973659
Descending Gradient...
w_0=-0.11377881499553, w_1=-0.078159667978339, w_2=-0.036764312973093, w_3=-0.048663766596054, w_4=-0.014328114868884, w_5=-0.031156603146767, w_6=0.028811819400376, w_7=0.0042133416102967, w_8=0.037757374947504, w_9=-0.024418325954552, w_10=-0.025323242029278, w_11=0.028054692435261, w_12=0.016421734828528
Pattern: {-0.2333, 0.4667, 0}
Forward propagating...
o_0=0.45134048114777, o_1=0.50159679376125, o_2=0.49600221352303, o_3=0.49394920087065
Back propagating...
e_0=-0.11176645941563, e_1=0.0021838850660863, e_2=0.0010271886019323, e_3=0.0013595450908201
Descending Gradient...
w_0=-0.12153309870358, w_1=-0.08209087387026, w_2=-0.040673189391242, w_3=-0.05266766200796, w_4=-0.015161203557947, w_5=-0.031250860837384, w_6=0.028591310016475, w_7=0.0032953279455422, w_8=0.037578145397303, w_9=-0.02482019971987, w_10=-0.026213494286707, w_11=0.027898339754269, w_12=0.0160669425535
Pattern: {0.4667, -0.7, 0}
Forward propagating...
o_0=0.44811380375222, o_1=0.48756259186452, o_2=0.50955063525365, o_3=0.49389025439372
Back propagating...
e_0=-0.11082204910041, e_1=0.0022729624326779, e_2=0.0011264603992445, e_3=0.0014589666767117
Descending Gradient...
w_0=-0.1479058126334, w_1=-0.095084679134638, w_2=-0.05407333113344, w_3=-0.065849605632637, w_4=-0.015513214952385, w_5=-0.031150054234656, w_6=0.028114413672962, w_7=0.0026662462171309, w_8=0.03750883963908, w_9=-0.025319877507564, w_10=-0.026759402149969, w_11=0.027876779797281, w_12=0.015568906088078
Pattern: {0.7, -0.7, 0}
Forward propagating...
o_0=0.4367440413023, o_1=0.48575427097607, o_2=0.51165947299535, o_3=0.49546415179466
Back propagating...
e_0=-0.10743845926948, e_1=0.0025518646638694, e_2=0.0014515990759447, e_3=0.0017685494872146
Descending Gradient...
w_0=-0.19044298554239, w_1=-0.1159121247026, w_2=-0.075753542155039, w_3=-0.087028938285961, w_4=-0.015383448891202, w_5=-0.030746724870878, w_6=0.027372603542475, w_7=0.0023541024998511, w_8=0.037624285343483, w_9=-0.025947408403291, w_10=-0.026941223066642, w_11=0.028074023148174, w_12=0.014904025957015
Pattern: {-0.7, -0.2333, 0}
Forward propagating...
o_0=0.41864106883829, o_1=0.4999383075283, o_2=0.4955177783564, o_3=0.48748507735577
Back propagating...
e_0=-0.10188916656406, e_1=0.002952547400205, e_2=0.0019294612522463, e_3=0.0022154376706011
Descending Gradient...
w_0=-0.2465570453092, w_1=-0.14357102777407, w_2=-0.104101113429, w_3=-0.11478249111669, w_4=-0.014749963641101, w_5=-0.030745415500002, w_6=0.026584429296056, w_7=0.0024108288734423, w_8=0.037491827474045, w_9=-0.026590961288722, w_10=-0.026717160299293, w_11=0.02798015104933, w_12=0.014215183057561
Pattern: {0.7, -0.2333, 0}
Forward propagating...
o_0=0.39487461288554, o_1=0.48938312059003, o_2=0.50871381249017, o_3=0.49738815956366
Back propagating...
e_0=-0.09435475684659, e_1=0.0033851254054998, e_2=0.0024548629885676, e_3=0.0027074946288964
Descending Gradient...
w_0=-0.31357178154748, w_1=-0.17654477497431, w_2=-0.13801385198991, w_3=-0.14797360296379, w_4=-0.013587429970048, w_5=-0.03032955920404, w_6=0.025736866266785, w_7=0.0028914836326738, w_8=0.03767333610765, w_9=-0.027270384804276, w_10=-0.026041692248621, w_11=0.02822733425241, w_12=0.013484684211092
Pattern: {-0.7, 0.7, 1}
Forward propagating...
o_0=0.36745354116635, o_1=0.50641441503771, o_2=0.48935932655707, o_3=0.49091061462863
Back propagating...
e_0=0.14702368192197, e_1=-0.0064879977470285, e_2=-0.0050705287076609, e_3=-0.0054371086009671
Descending Gradient...
w_0=-0.34815589982558, w_1=-0.19319153787602, w_2=-0.15594451994941, w_3=-0.16521489356616, w_4=-0.013676549271831, w_5=-0.029160508813663, w_6=0.024179279816431, w_7=0.0024367303921414, w_8=0.038457833644584, w_9=-0.028503005734962, w_10=-0.026385265008186, w_11=0.0291158449388, w_12=0.012161189445651
Pattern: {-0.4667, 0.4667, 1}
Forward propagating...
o_0=0.35358144144306, o_1=0.50280425311699, o_2=0.49279702500663, o_3=0.49142633977272
Back propagating...
e_0=0.14774646370459, e_1=-0.007135617174368, e_2=-0.0057588674452825, e_3=-0.0061006847533577
Descending Gradient...
w_0=-0.35342597512757, w_1=-0.19517330317917, w_2=-0.15934054300341, w_3=-0.16802591693056, w_4=-0.015005489648949, w_5=-0.027525579768651, w_6=0.022194668317438, w_7=0.0010196506727379, w_8=0.039634222529248, w_9=-0.030082705674005, w_10=-0.027762100323633, w_11=0.03041376273207, w_12=0.010471785981235
Pattern: {0.7, -0.4667, 0}
Forward propagating...
o_0=0.35120512955616, o_1=0.48884394003185, o_2=0.51069916783693, o_3=0.49716011830636
Back propagating...
e_0=-0.080025631210306, e_1=0.0039027728077479, e_2=0.0031863722103917, e_3=0.0033614865714272
Descending Gradient...
w_0=-0.37217352836117, w_1=-0.20380289980327, w_2=-0.16954904282334, w_3=-0.17751830960754, w_4=-0.015518550747, w_5=-0.02557605395919, w_6=0.020089768756204, w_7=0.00030189406209323, w_8=0.04108330312122, w_9=-0.031764674603497, w_10=-0.028412991957534, w_11=0.031993670851013, w_12=0.0086767818512561
Pattern: {0.4667, 0.4667, 1}
Forward propagating...
o_0=0.34378633698578, o_1=0.49548037308995, o_2=0.50116272240194, o_3=0.49764199456116
Back propagating...
e_0=0.14804002501322, e_1=-0.0075421302925948, e_2=-0.0062749772017964, e_3=-0.0065698076278958
Descending Gradient...
w_0=-0.36313932189409, w_1=-0.19873312457044, w_2=-0.16575306781826, w_3=-0.17316904968539, w_4=-0.01730017853645, w_5=-0.024437465366998, w_6=0.017579374514771, w_7=-0.0014422078978013, w_8=0.04187498257848, w_9=-0.033790939715553, w_10=-0.030148510762928, w_11=0.032879015544573, w_12=0.0065247055207858
Pattern: {-0.2333, 0.2333, 1}
Forward propagating...
o_0=0.34768470239013, o_1=0.49812559633275, o_2=0.49522637815401, o_3=0.49092675329955
Back propagating...
e_0=0.14794514218806, e_1=-0.0073502967937504, e_2=-0.0061300314941596, e_3=-0.0064027708232092
Descending Gradient...
w_0=-0.32911813619081, w_1=-0.18127365597993, w_2=-0.14951508135071, w_3=-0.15654442579931, w_4=-0.020189945485861, w_5=-0.023112641391677, w_6=0.015019925455135, w_7=-0.0040846551731843, w_8=0.042837767950842, w_9=-0.035864852177231, w_10=-0.032830962581843, w_11=0.03393723489456, w_12=0.0043264276975779
Pattern: {0, 0.2333, 0}
Forward propagating...
o_0=0.36116348329866, o_1=0.49582864756113, o_2=0.49688705892527, o_3=0.49204526949507
Back propagating...
e_0=-0.083329235798047, e_1=0.0037760859691679, e_2=0.0031146236348076, e_3=0.003260356401742
Descending Gradient...
w_0=-0.31308168532252, w_1=-0.17279061314888, w_2=-0.14214680683711, w_3=-0.14875757165172, w_4=-0.022129920695726, w_5=-0.021920299813889, w_6=0.012870589451369, w_7=-0.0059177985849377, w_8=0.043704274785968, w_9=-0.037604211096292, w_10=-0.034674606848563, w_11=0.034889632309549, w_12=0.0024810898576829
Pattern: {-0.7, -0.7, 0}
Forward propagating...
o_0=0.36781007528887, o_1=0.49605130123456, o_2=0.49745306123739, o_3=0.48479616046987
Back propagating...
e_0=-0.085525340760275, e_1=0.003694263595951, e_2=0.0030392096609749, e_3=0.0031776946002566
Descending Gradient...
w_0=-0.31361581417411, w_1=-0.17258024200115, w_2=-0.14296070722541, w_3=-0.149005315363, w_4=-0.023229402255314, w_5=-0.021299739684384, w_6=0.010483639757475, w_7=-0.0070357659648451, w_8=0.044111827754112, w_9=-0.039541937306916, w_10=-0.035777790133565, w_11=0.035357522394508, w_12=0.00043101821324601
Pattern: {0.2333, -0.2333, 1}
Forward propagating...
o_0=0.36726134110932, o_1=0.4923394833094, o_2=0.5031201238551, o_3=0.49309308020442
Back propagating...
e_0=0.14703609329575, e_1=-0.0063423920159702, e_2=-0.0052548913342344, e_3=-0.0054762446745133
Descending Gradient...
w_0=-0.28836521381378, w_1=-0.15972236498301, w_2=-0.13074727451761, w_3=-0.13654035067788, w_4=-0.025328854261738, w_5=-0.021000179577861, w_6=0.0085943290430024, w_7=-0.0089615425902528, w_8=0.044264081349493, w_9=-0.041071346820529, w_10=-0.037728997908107, w_11=0.035555042091522, w_12=-0.0011904648872985
Pattern: {0.4667, -0.2333, 0}
Forward propagating...
o_0=0.37745345980959, o_1=0.49071739293147, o_2=0.50531941164181, o_3=0.49478575795786
Back propagating...
e_0=-0.088694899298377, e_1=0.0035404190824891, e_2=0.002898825947237, e_3=0.0030272789010657
Descending Gradient...
w_0=-0.2811612808667, w_1=-0.15576699837294, w_2=-0.12759855458818, w_3=-0.13300175273213, w_4=-0.026598787728083, w_5=-0.020441420604476, w_6=0.0067494029398869, w_7=-0.010187447012353, w_8=0.044637863947512, w_9=-0.042566167199141, w_10=-0.038955311097508, w_11=0.035980055254882, w_12=-0.0027733959071218
Pattern: {0.2333, -0.4667, 1}
Forward propagating...
o_0=0.38044290792613, o_1=0.49137142733202, o_2=0.5050228802442, o_3=0.49268381712944
Back propagating...
e_0=0.14603338697491, e_1=-0.0056851020085509, e_2=-0.0046579421604967, e_3=-0.0048546344766901
Descending Gradient...
w_0=-0.24912189849371, w_1=-0.13964975750957, w_2=-0.11185842135386, w_3=-0.1172260644394, w_4=-0.028736620699291, w_5=-0.020170646030684, w_6=0.0055532859408763, w_7=-0.012105900870331, w_8=0.044784096152171, w_9=-0.043531079758789, w_10=-0.04090855400139, w_11=0.036164364512809, w_12=-0.0038015436906653
Pattern: {-0.4667, 0, 1}
Forward propagating...
o_0=0.39407894546172, o_1=0.49516940525285, o_2=0.49174908942168, o_3=0.4855574030304
Back propagating...
e_0=0.14468227184954, e_1=-0.0050507395720518, e_2=-0.0040448808698037, e_3=-0.0042365955567445
Descending Gradient...
w_0=-0.19496705678436, w_1=-0.11260684969463, w_2=-0.085241510741418, w_3=-0.090733924043784, w_4=-0.031544549798487, w_5=-0.019514442386572, w_6=0.0044767806417668, w_7=-0.014540363494726, w_8=0.045246060669204, w_9=-0.044399501062473, w_10=-0.043407876837314, w_11=0.036676256195552, w_12=-0.0047268766958545
Pattern: {0.4667, -0.4667, 0}
Forward propagating...
o_0=0.41627338833071, o_1=0.48931631298046, o_2=0.50682388131872, o_3=0.493979032376
Back propagating...
e_0=-0.10115021006203, e_1=0.0028462515337811, e_2=0.0021551476837129, e_3=0.0022941061567344
Descending Gradient...
w_0=-0.1639289860068, w_1=-0.096929761034011, w_2=-0.070257726050692, w_3=-0.075635062193665, w_4=-0.033573591969351, w_5=-0.018691398628479, w_6=0.0032754653941756, w_7=-0.016354229012032, w_8=0.045837845033731, w_9=-0.045357096534986, w_10=-0.045255798812217, w_11=0.037324324095106, w_12=-0.0057470417856106
Pattern: {0.2333, 0.2333, 1}
Forward propagating...
o_0=0.42961110200726, o_1=0.49070853744852, o_2=0.49593957166618, o_3=0.4905289282869
Back propagating...
e_0=0.13977117739781, e_1=-0.0033858270911586, e_2=-0.0024548393696571, e_3=-0.0026419521384897
Descending Gradient...
w_0=-0.11153476626238, w_1=-0.070817671982746, w_2=-0.044641659705298, w_3=-0.050047770504047, w_4=-0.035992249664082, w_5=-0.01808889410176, w_6=0.0020560468157791, w_7=-0.018416304867297, w_8=0.04627022600744, w_9=-0.046319157414612, w_10=-0.047381270213866, w_11=0.037799720903771, w_12=-0.0067730546673254
Pattern: {-0.4667, 0.7, 0}
Forward propagating...
o_0=0.45211087269845, o_1=0.49347263834426, o_2=0.48189940593934, o_3=0.48256618566355
Back propagating...
e_0=-0.11199086133446, e_1=0.0019823951118996, e_2=0.0012482265005242, e_3=0.0013995196923677
Descending Gradient...
w_0=-0.083978369225927, w_1=-0.056988066353911, w_2=-0.031031657665292, w_3=-0.036476733470477, w_4=-0.037822122444758, w_5=-0.017708547192489, w_6=0.00120141349643, w_7=-0.020053733499444, w_8=0.046557423104915, w_9=-0.047032104459962, w_10=-0.049049278529185, w_11=0.038113275759494, w_12=-0.0075250250985536
Pattern: {0.2333, 0, 1}
Forward propagating...
o_0=0.46376575344719, o_1=0.48951315648505, o_2=0.49770204450738, o_3=0.48996198609937
Back propagating...
e_0=0.13335452863701, e_1=-0.0018990684222497, e_2=-0.0010345311679546, e_3=-0.0012155942605054
Descending Gradient...
w_0=-0.035840569381645, w_1=-0.033117631945141, w_2=-0.0071677620585695, w_3=-0.012828536441656, w_4=-0.039801344921259, w_5=-0.017443769190154, w_6=0.00043224350901584, w_7=-0.021708462222769, w_8=0.046773663171383, w_9=-0.047673756800776, w_10=-0.050763215008561, w_11=0.038345845454974, w_12=-0.0082017984866589
Pattern: {0.4667, 0, 1}
Forward propagating...
o_0=0.48453106502369, o_1=0.48801670718054, o_2=0.50003020159479, o_3=0.49178393737215
Back propagating...
e_0=0.1287438882397, e_1=-0.0010653109131602, e_2=-0.00023070138850758, e_3=-0.00041278742668737
Descending Gradient...
w_0=0.030013630920156, w_1=-0.00063913650578575, w_2=0.025575514655835, w_3=0.01953482173173, w_4=-0.041769074559913, w_5=-0.017292475593608, w_6=-0.00026000947965692, w_7=-0.02323809081675, w_8=0.046949437272051, w_9=-0.048251243907509, w_10=-0.05237799563967, w_11=0.0385214447998, w_12=-0.0088108945359538
Pattern: {-0.4667, -0.2333, 0}
Forward propagating...
o_0=0.5129232443123, o_1=0.49159128887054, o_2=0.49152771649207, o_3=0.48293154170507
Back propagating...
e_0=-0.12814514764212, e_1=2.0469769459797e-05, e_2=-0.00081910927654944, e_3=-0.00062509386382733
Descending Gradient...
w_0=0.066857010354407, w_1=0.017567377688553, w_2=0.044021757633787, w_3=0.037831910688031, w_4=-0.043536449025047, w_5=-0.017157983173963, w_6=-0.00088387289897503, w_7=-0.024758100674729, w_8=0.047174532665041, w_9=-0.048737540119581, w_10=-0.053940689633837, w_11=0.038730537188737, w_12=-0.0093335599605937
Pattern: {-0.7, 0, 0}
Forward propagating...
o_0=0.52872513413313, o_1=0.49211918750346, o_2=0.48555894908432, o_3=0.47974806935225
Back propagating...
e_0=-0.13174501480219, e_1=-0.00057845986659043, e_2=-0.0014487022964443, e_3=-0.0012439971992407
Descending Gradient...
w_0=0.076960674254849, w_1=0.022607246776093, w_2=0.049428631400414, w_3=0.043238517861529, w_4=-0.04522831652032, w_5=-0.016966078662625, w_6=-0.0014453499763613, w_7=-0.026379632448787, w_8=0.047554584550046, w_9=-0.049175206710445, w_10=-0.055564813738455, w_11=0.039071109995687, w_12=-0.0098039588427697
Pattern: {0, 0, 1}
Forward propagating...
o_0=0.53330457718469, o_1=0.48869484795638, o_2=0.49340547430267, o_3=0.48611236949356
Back propagating...
e_0=0.11615619953898, e_1=0.00065615735071208, e_2=0.0014351108104681, e_3=0.0012546368212879
Descending Gradient...
w_0=0.10638130668457, w_1=0.037076992802635, w_2=0.064324436117556, w_3=0.057985833260798, w_4=-0.046636169729692, w_5=-0.016793364602421, w_6=-0.001950679346009, w_7=-0.027587866653608, w_8=0.047896631246551, w_9=-0.049569106642223, w_10=-0.056806963988885, w_11=0.039377625521942, w_12=-0.010227317836728
Pattern: {-0.4667, -0.7, 0}
Forward propagating...
o_0=0.54599389176198, o_1=0.49064278488989, o_2=0.49618936132975, o_3=0.4830002101372
Back propagating...
e_0=-0.13534345667074, e_1=-0.0012540927175689, e_2=-0.0021763464651722, e_3=-0.0019597327610341
Descending Gradient...
w_0=0.10917477095394, w_1=0.038478838389451, w_2=0.065978363281002, w_3=0.059818506467924, w_4=-0.048122703843701, w_5=-0.016535497060761, w_6=-0.0022518494207897, w_7=-0.029056138069352, w_8=0.048382220930082, w_9=-0.04965701413884, w_10=-0.058267852447454, w_11=0.039813545769497, w_12=-0.010368273668064
Pattern: {-0.2333, -0.7, 1}
Forward propagating...
o_0=0.54733493910955, o_1=0.489329450937, o_2=0.49860405354821, o_3=0.48492992557402
Back propagating...
e_0=0.11215202548939, e_1=0.0010783785527854, e_2=0.0018498873507433, e_3=0.0016756680567009
Descending Gradient...
w_0=0.13131549325701, w_1=0.04934437500207, w_2=0.077252802269567, w_3=0.070985440194708, w_4=-0.049271868299571, w_5=-0.016347443773632, w_6=-0.0026550038608086, w_7=-0.030053852057142, w_8=0.048743725369448, w_9=-0.04996274208626, w_10=-0.059289410150243, w_11=0.040137460654712, w_12=-0.010700403253212
Pattern: {-0.2333, 0.7, 0}
Forward propagating...
o_0=0.55643296937962, o_1=0.48817307838616, o_2=0.48090936429783, o_3=0.48097325150072
Back propagating...
e_0=-0.13733618137762, e_1=-0.0016932441010993, e_2=-0.002648534520452, e_3=-0.0024336880644792
Descending Gradient...
w_0=0.1272083115887, w_1=0.047390688326966, w_2=0.07584170261503, w_3=0.069476050350284, w_4=-0.050602434027547, w_5=-0.016109064891678, w_6=-0.0032252652592102, w_7=-0.031415288187232, w_8=0.049177212408011, w_9=-0.050562342717695, w_10=-0.060634707494037, w_11=0.040528345450857, w_12=-0.011297446667744
Pattern: {0, 0.7, 0}
Forward propagating...
o_0=0.55489781556213, o_1=0.48678804632438, o_2=0.48330397764692, o_3=0.48287097563591
Back propagating...
e_0=-0.13705211941575, e_1=-0.0016226148305438, e_2=-0.0025956690447535, e_3=-0.0023776662463497
Descending Gradient...
w_0=0.099527727189455, w_1=0.033957186964747, w_2=0.062980091895696, w_3=0.056536363632632, w_4=-0.052083900778071, w_5=-0.015894523897919, w_6=-0.0039372708345133, w_7=-0.033094822787144, w_8=0.049567350742717, w_9=-0.051419952743968, w_10=-0.062261566696563, w_11=0.040880141767389, w_12=-0.012126049856001
Pattern: {0.7, 0.4667, 1}
Forward propagating...
o_0=0.54359017649523, o_1=0.48374383355421, o_2=0.49440139169453, o_3=0.49017509107725
Back propagating...
e_0=0.1132352299791, e_1=0.00096027133820942, e_2=0.0017826677627399, e_3=0.0015998590657943
Descending Gradient...
w_0=0.094431366476481, w_1=0.031452983481359, w_2=0.061201781924137, w_3=0.054604036191174, w_4=-0.053249173369355, w_5=-0.015583803764605, w_6=-0.0044996480914162, w_7=-0.034294437068586, w_8=0.050136852044889, w_9=-0.052046206834761, w_10=-0.063445764642322, w_11=0.041392741187826, w_12=-0.012741128235881
Pattern: {-0.2333, -0.2333, 1}
Forward propagating...
o_0=0.54145565440884, o_1=0.48786145955495, o_2=0.49153856172927, o_3=0.48247463575859
Back propagating...
e_0=0.11384804525372, e_1=0.00089468755276279, e_2=0.0017414269502805, e_3=0.0015522313507364
Descending Gradient...
w_0=0.1097680497542, w_1=0.038919063213178, w_2=0.069394426223181, w_3=0.062477480472844, w_4=-0.054141348379778, w_5=-0.015340683500683, w_6=-0.0050423154786892, w_7=-0.035069340205584, w_8=0.050578305108031, w_9=-0.052680933625288, w_10=-0.064239902307127, w_11=0.041790706940748, w_12=-0.013358072503245
Pattern: {0.7, 0.7, 1}
Forward propagating...
o_0=0.54814336434471, o_1=0.48290430467479, o_2=0.49086572132024, o_3=0.48891755085684
Back propagating...
e_0=0.11191685304558, e_1=0.0010876517607725, e_2=0.0019409534600175, e_3=0.0017472119532384
Descending Gradient...
w_0=0.14315651398713, w_1=0.055096432739554, w_2=0.08638163178199, w_3=0.079139250222212, w_4=-0.054753966831023, w_5=-0.014988637922459, w_6=-0.0053974787865403, w_7=-0.03542708617338, w_8=0.051213379663711, w_9=-0.05301442093791, w_10=-0.064648864113634, w_11=0.04236290958265, w_12=-0.013699288879601
Pattern: {-0.7, 0.2333, 1}
Forward propagating...
o_0=0.56195632301902, o_1=0.48862167673395, o_2=0.47910100437195, o_3=0.47564455437665
Back propagating...
e_0=0.10782945093603, e_1=0.0014844853614339, e_2=0.002324552712817, e_3=0.0021283234823767
Descending Gradient...
w_0=0.19207628571057, w_1=0.078876431558883, w_2=0.11071082647768, w_3=0.10311032894599, w_4=-0.055045538498893, w_5=-0.014853646358833, w_6=-0.0056565179375123, w_7=-0.035342260819653, w_8=0.051500189056502, w_9=-0.053219653843387, w_10=-0.064644473130075, w_11=0.04261717233377, w_12=-0.013919489491344
Pattern: {-0.7, -0.4667, 0}
Forward propagating...
o_0=0.58274255219136, o_1=0.48949952183794, o_2=0.48836340645839, o_3=0.47801910980717
Back propagating...
e_0=-0.14169599026363, e_1=-0.0027928862010522, e_2=-0.0039196958282029, e_3=-0.0036455209261244
Descending Gradient...
w_0=0.21130728196554, w_1=0.08814040958721, w_2=0.12049725281863, w_3=0.11283095634981, w_4=-0.055796708085159, w_5=-0.01439002539194, w_6=-0.0056615511751317, w_7=-0.035951864771234, w_8=0.05223848024897, w_9=-0.053084232100787, w_10=-0.065278487406943, w_11=0.043292585123228, w_12=-0.013819931234075
Pattern: {-0.4667, 0.2333, 1}
Forward propagating...
o_0=0.59055037649147, o_1=0.48740223598315, o_2=0.48182897739011, o_3=0.47783769929407
Back propagating...
e_0=0.099005176638075, e_1=0.0021802043002832, e_2=0.0029785238791336, e_3=0.002787225432243
Descending Gradient...
w_0=0.24594108450666, w_1=0.10492267509448, w_2=0.13765316005326, w_3=0.12985849203226, w_4=-0.05609122496025, w_5=-0.014150829257452, w_6=-0.0055770687979193, w_7=-0.035979266648809, w_8=0.052659678830672, w_9=-0.052840746848772, w_10=-0.065361335805482, w_11=0.043672816964626, w_12=-0.013616533356197
Pattern: {0.2333, 0.7, 0}
Forward propagating...
o_0=0.60499242486178, o_1=0.48418114071317, o_2=0.4848340819602, o_3=0.4838296309568
Back propagating...
e_0=-0.14457902710589, e_1=-0.0037886085823358, e_2=-0.0049708624839458, e_3=-0.004688794355709
Descending Gradient...
w_0=0.25181017705015, w_1=0.10777628735424, w_2=0.14082652958586, w_3=0.13294174111393, w_4=-0.05701929664974, w_5=-0.014090232153308, w_6=-0.0059651392097643, w_7=-0.036873829273317, w_8=0.05283580966614, w_9=-0.053230540776242, w_10=-0.066256438376416, w_11=0.043823593870326, w_12=-0.014007852574682
Pattern: {-0.2333, -0.4667, 1}
Forward propagating...
o_0=0.60778924567122, o_1=0.48726572566677, o_2=0.4939108684813, o_3=0.48252137040386
Back propagating...
e_0=0.093495779507409, e_1=0.0025175229560921, e_2=0.0032911833516339, e_3=0.0031035756879298
Descending Gradient...
w_0=0.27345412175308, w_1=0.11831706393651, w_2=0.15176381395496, w_3=0.14361156482705, w_4=-0.057413994652965, w_5=-0.014138478928068, w_6=-0.0065200149740563, w_7=-0.037102978548838, w_8=0.052859956629773, w_9=-0.053850154483252, w_10=-0.066518904944869, w_11=0.043832581849057, w_12=-0.01461351665669
Pattern: {0, -0.4667, 1}
Forward propagating...
o_0=0.61682547748538, o_1=0.48641057169374, o_2=0.49700725787724, o_3=0.48507973680498
Back propagating...
e_0=0.090563991103182, e_1=0.0026768375658914, e_2=0.0034359610729745, e_3=0.0032486137907219
Descending Gradient...
w_0=0.30878237042878, w_1=0.13551273733084, w_2=0.16948428804126, w_3=0.16090228863831, w_4=-0.057300776281837, w_5=-0.014181901025352, w_6=-0.0072380271780193, w_7=-0.036707919709037, w_8=0.052881688897043, w_9=-0.054688430350292, w_10=-0.0661866174431, w_11=0.043840671029915, w_12=-0.015423936740321
Pattern: {0.4667, 0.2333, 1}
Forward propagating...
o_0=0.6309923218046, o_1=0.48360385559871, o_2=0.49380360567044, o_3=0.48767135426475
Back propagating...
e_0=0.085920121089607, e_1=0.0029076875983252, e_2=0.0036399685211804, e_3=0.0034540847318759
Descending Gradient...
w_0=0.35561381542759, w_1=0.15826032120641, w_2=0.19285755619783, w_3=0.18379657688526, w_4=-0.056690034418115, w_5=-0.013983502797533, w_6=-0.0077655245461654, w_7=-0.035715372262009, w_8=0.053198533266632, w_9=-0.055294267815831, w_10=-0.06528309386343, w_11=0.044130055027952, w_12=-0.016012293171197
Pattern: {0, -0.2333, 1}
Forward propagating...
o_0=0.64952983486356, o_1=0.48628385777285, o_2=0.49429644251079, o_3=0.48461799892159
Back propagating...
e_0=0.079781318751171, e_1=0.0031541788804361, e_2=0.0038461070118345, e_3=0.0036624138421356
Descending Gradient...
w_0=0.41172384670797, w_1=0.18552251100002, w_2=0.22079473139531, w_3=0.2111675423403, w_4=-0.055588385436688, w_5=-0.013804944392496, w_6=-0.0083690494157379, w_7=-0.034149010832612, w_8=0.053483693199262, w_9=-0.055996548468841, w_10=-0.063829000219354, w_11=0.044390500626184, w_12=-0.016691341160126

---Epoch 2---
Pattern: {0, -0.7, 1}
Forward propagating...
o_0=0.67165648504334, o_1=0.48757004886951, o_2=0.5012621405931, o_3=0.48696668776237
Back propagating...
e_0=0.072410925519782, e_1=0.0033563886011969, e_2=0.0039969622437687, e_3=0.0038201118830259
Descending Gradient...
w_0=0.47489478682627, w_1=0.21623692655078, w_2=0.2522901387905, w_3=0.24197221024753, w_4=-0.054009533348195, w_5=-0.013644241827963, w_6=-0.0093233794019997, w_7=-0.032039817153496, w_8=0.053740337138628, w_9=-0.057118228931412, w_10=-0.061851796360155, w_11=0.044624901664594, w_12=-0.017770448055833
Pattern: {0.2333, -0.7, 1}
Forward propagating...
o_0=0.6955802155404, o_1=0.48733611663897, o_2=0.50511996197399, o_3=0.49025086247579
Back propagating...
e_0=0.06446039598288, e_1=0.0034824440707612, e_2=0.0040652542510792, e_3=0.0038979236354876
Descending Gradient...
w_0=0.54302920222975, w_1=0.24937732938114, w_2=0.28633404618053, w_3=0.2752267201911, w_4=-0.051979138756168, w_5=-0.013357430034585, w_6=-0.010608875788304, w_7=-0.029430123348353, w_8=0.054137290851995, w_9=-0.058625734993483, w_10=-0.059390176250666, w_11=0.04499500507639, w_12=-0.019219139907316
Pattern: {0.4667, 0.7, 0}
Forward propagating...
o_0=0.71861579751498, o_1=0.48359607318687, o_2=0.48870135770794, o_3=0.48704180100718
Back propagating...
e_0=-0.14530924019927, e_1=-0.0090494566381152, e_2=-0.010396434154399, e_3=-0.0099915309793541
Descending Gradient...
w_0=0.57892105905801, w_1=0.2669062707858, w_2=0.30454631881129, w_3=0.29277073618163, w_4=-0.051735438535013, w_5=-0.01383839116782, w_6=-0.012874380974146, w_7=-0.028900774900744, w_8=0.053645446425549, w_9=-0.06125605363326, w_10=-0.058923236073513, w_11=0.044512064833096, w_12=-0.021746925118622
Pattern: {0.7, 0, 0}
Forward propagating...
o_0=0.73215075079832, o_1=0.48464924775761, o_2=0.5021627459109, o_3=0.49305924819766
Back propagating...
e_0=-0.14357917629798, e_1=-0.0095715151735713, e_2=-0.010931422870445, e_3=-0.010506920253061
Descending Gradient...
w_0=0.5860973743513, w_1=0.27050484858735, w_2=0.30831984432953, w_3=0.2961715684467, w_4=-0.053191123491349, w_5=-0.015443766796495, w_6=-0.014913335641405, w_7=-0.030337360300223, w_8=0.051863687140118, w_9=-0.06362334040906, w_10=-0.060341700958361, w_11=0.042790320883131, w_12=-0.024021931808797
Pattern: {0, 0.4667, 0}
Forward propagating...
o_0=0.73294332398701, o_1=0.48496673815194, o_2=0.48499691189665, o_3=0.4821194439462
Back propagating...
e_0=-0.14346442630878, e_1=-0.0096931852013932, e_2=-0.011048275889132, e_3=-0.010608936352177
Descending Gradient...
w_0=0.56744978351122, w_1=0.26156786050689, w_2=0.29953955164376, w_3=0.2871280943336, w_4=-0.056197547362296, w_5=-0.016888604862302, w_6=-0.017540061510298, w_7=-0.033563735440353, w_8=0.050260103783231, w_9=-0.066656238819835, w_10=-0.063474883216355, w_11=0.041240751328162, w_12=-0.026935896184178
Pattern: {0.2333, 0.4667, 0}
Forward propagating...
o_0=0.72678490044821, o_1=0.48292574013824, o_2=0.48676646138669, o_3=0.48340000342415
Back propagating...
e_0=-0.14431666667238, e_1=-0.0094261455711752, e_2=-0.010799566940933, e_3=-0.010347923893731
Descending Gradient...
w_0=0.52541153508749, w_1=0.24132808044774, w_2=0.2793437984244, w_3=0.26678049912819, w_4=-0.060552904321103, w_5=-0.018573805079835, w_6=-0.020673971666464, w_7=-0.038357397281133, w_8=0.048375959442751, w_9=-0.070267875020516, w_10=-0.068105633929952, w_11=0.039423658865919, w_12=-0.030403604936231
Pattern: {-0.4667, -0.4667, 0}
Forward propagating...
o_0=0.71296002480286, o_1=0.48944257765343, o_2=0.49296535414247, o_3=0.48192905121029
Back propagating...
e_0=-0.14590586300179, e_1=-0.0087988708520893, e_2=-0.01018745754061, e_3=-0.0097184984754494
Descending Gradient...
w_0=0.46204358548081, w_1=0.21061508360009, w_2=0.2485804768274, w_3=0.23616231547189, w_4=-0.066012527983145, w_5=-0.019371859495948, w_6=-0.022775865027346, w_7=-0.044454498007442, w_8=0.047512264662305, w_9=-0.072686312475143, w_10=-0.073974046805394, w_11=0.038582009716637, w_12=-0.032730808746343
Pattern: {-0.2333, 0, 1}
Forward propagating...
o_0=0.68957625593923, o_1=0.48463157424872, o_2=0.48611879063467, o_3=0.47926808596071
Back propagating...
e_0=0.066449568398003, e_1=0.0034955148261711, e_2=0.004126333516791, e_3=0.0039164759898391
Descending Gradient...
w_0=0.41664110530446, w_1=0.18860900925186, w_2=0.22654640455998, w_3=0.21417920273654, w_4=-0.070314474184403, w_5=-0.020232821602015, w_6=-0.024667569052139, w_7=-0.049219780295681, w_8=0.046566471478247, w_9=-0.074862906184308, w_10=-0.078570235095069, w_11=0.037664625558807, w_12=-0.034825292175444
Pattern: {0.7, 0.2333, 1}
Forward propagating...
o_0=0.67302456591436, o_1=0.4774571947104, o_2=0.49147863359914, o_3=0.48492213846799
Back propagating...
e_0=0.071955031329459, e_1=0.003385945121254, e_2=0.0040741047225815, e_3=0.0038493141829417
Descending Gradient...
w_0=0.38837100362839, w_1=0.17481574563413, w_2=0.21290450260301, w_3=0.20050060411625, w_4=-0.073593685369316, w_5=-0.020592909220122, w_6=-0.026231863000016, w_7=-0.052795566028645, w_8=0.04621433544111, w_9=-0.076655505011995, w_10=-0.082033174573762, w_11=0.037310520804171, w_12=-0.036553169386831
Pattern: {-0.7, 0.4667, 1}
Forward propagating...
o_0=0.66075601425279, o_1=0.48215232121354, o_2=0.46980659999022, o_3=0.46873835559753
Back propagating...
e_0=0.076044085051926, e_1=0.0033191912858755, e_2=0.0040327724348523, e_3=0.0037968206135979
Descending Gradient...
w_0=0.37623562700402, w_1=0.16881815399958, w_2=0.20687884312507, w_3=0.19442770174951, w_4=-0.07596411696071, w_5=-0.021323589008938, w_6=-0.027368640902809, w_7=-0.055308038012214, w_8=0.045403398384418, w_9=-0.077939477350228, w_10=-0.084485376497206, w_11=0.036526715999833, w_12=-0.037798163045515
Pattern: {-0.2333, 0.4667, 0}
Forward propagating...
o_0=0.65635826160633, o_1=0.47907166778415, o_2=0.47445351328207, o_3=0.47236632168053
Back propagating...
e_0=-0.14804298033752, e_1=-0.0062371391399411, e_2=-0.0076367522679092, e_3=-0.0071739343259642
Descending Gradient...
w_0=0.33940626648302, w_1=0.15100876196703, w_2=0.1891638349708, w_3=0.17672424895674, w_4=-0.079189004742453, w_5=-0.021726554020636, w_6=-0.02890114376173, w_7=-0.058905694444309, w_8=0.044985344536613, w_9=-0.079718765104238, w_10=-0.08794779673535, w_11=0.036114185479621, w_12=-0.039504570489567
Pattern: {0.4667, -0.7, 0}
Forward propagating...
o_0=0.6443223520602, o_1=0.48273237313846, o_2=0.50447290603167, o_3=0.4891416806985
Back propagating...
e_0=-0.14766003556301, e_1=-0.0055678411872084, e_2=-0.0069824258185784, e_3=-0.0065207005272679
Descending Gradient...
w_0=0.28041933579059, w_1=0.12250626024536, w_2=0.16018449236404, w_3=0.14815147279896, w_4=-0.083065775953784, w_5=-0.022543962040527, w_6=-0.029598335789325, w_7=-0.063365509751446, w_8=0.044038823900921, w_9=-0.080464776920071, w_10=-0.092205097541951, w_11=0.035210346097618, w_12=-0.040241551374625
Pattern: {0.7, -0.7, 0}
Forward propagating...
o_0=0.620799418084, o_1=0.48047800049992, o_2=0.50594647232144, o_3=0.49015408061418
Back propagating...
e_0=-0.14614083937923, e_1=-0.0044689688766148, e_2=-0.0058515462701407, e_3=-0.0054106462553838
Descending Gradient...
w_0=0.20175645127604, w_1=0.084565953493996, w_2=0.1211636816424, w_3=0.10990045672289, w_4=-0.087336939597389, w_5=-0.023827077945814, w_6=-0.029678359926776, w_7=-0.068403364125145, w_8=0.042470140910706, w_9=-0.080419373136229, w_10=-0.096983531362584, w_11=0.033734086487531, w_12=-0.040242030004892
Pattern: {-0.7, -0.2333, 0}
Forward propagating...
o_0=0.58728895101682, o_1=0.48407188541991, o_2=0.48016775458062, o_3=0.47222638653318
Back propagating...
e_0=-0.14234747124294, e_1=-0.0030063833730063, e_2=-0.0043050522320632, e_3=-0.0038989456168695
Descending Gradient...
w_0=0.10604904774543, w_1=0.038361055879638, w_2=0.074083585506461, w_3=0.063711001658424, w_4=-0.09170710396691, w_5=-0.024613600297379, w_6=-0.02962763853332, w_7=-0.073690817202084, w_8=0.04158569511794, w_9=-0.080202745210767, w_10=-0.10196643728411, w_11=0.032883073676518, w_12=-0.040083276569959
Pattern: {0.7, -0.2333, 0}
Forward propagating...
o_0=0.54774461127877, o_1=0.47451597740102, o_2=0.49353297811733, o_3=0.48260780535874
Back propagating...
e_0=-0.13568754273794, e_1=-0.0012978989647378, e_2=-0.002512634510976, e_3=-0.0021585823663317
Descending Gradient...
w_0=-0.0038329354112628, w_1=-0.014490885691886, w_2=0.019992400498462, w_3=0.010680815337729, w_4=-0.095867384218308, w_5=-0.025480463036968, w_6=-0.029528999309227, w_7=-0.07888923601075, w_8=0.040481896176856, w_9=-0.079905195492354, w_10=-0.10682880452758, w_11=0.031852735806732, w_12=-0.039852268956959
Pattern: {-0.7, 0.7, 1}
Forward propagating...
o_0=0.50084584876359, o_1=0.47534467277961, o_2=0.45930019988599, o_3=0.46082488180347
Back propagating...
e_0=0.12478818068421, e_1=-0.00045097358207458, e_2=0.00061957122544798, e_3=0.00033116438323303
Descending Gradient...
w_0=-0.080888788632547, w_1=-0.051677088646291, w_2=-0.018659499650696, w_3=-0.0269828900934, w_4=-0.099690556821429, w_5=-0.026205395238794, w_6=-0.029495468271347, w_7=-0.083459387974096, w_8=0.039412579654763, w_9=-0.079561503270664, w_10=-0.11114698127965, w_11=0.030884864086978, w_12=-0.039603794468312
Pattern: {-0.4667, 0.4667, 1}
Forward propagating...
o_0=0.46838608757001, o_1=0.47471507844201, o_2=0.46530967584241, o_3=0.46405112661295
Back propagating...
e_0=0.13237216218639, e_1=-0.0017057786027707, e_2=-0.00061452713663089, e_3=-0.00088832998331799
Descending Gradient...
w_0=-0.12707392814908, w_1=-0.074147835567981, w_2=-0.042667251406374, w_3=-0.050130421057329, w_4=-0.10342992341972, w_5=-0.026718519017503, w_6=-0.02960460554019, w_7=-0.087680066990018, w_8=0.038500384752446, w_9=-0.079302370238711, w_10=-0.11518879810359, w_11=0.030086331669762, w_12=-0.039452719559093
Pattern: {0.7, -0.4667, 0}
Forward propagating...
o_0=0.44835007051453, o_1=0.47294733998789, o_2=0.49407043263153, o_3=0.48108009250333
Back propagating...
e_0=-0.11089144732349, e_1=0.0020495726952441, e_2=0.0011826919593407, e_3=0.0013877688082271
Descending Gradient...
w_0=-0.18804655699558, w_1=-0.10354952542934, w_2=-0.073862160423478, w_3=-0.080299040778701, w_4=-0.10643667813652, w_5=-0.026929257763173, w_6=-0.029870222808101, w_7=-0.091271707011464, w_8=0.03782428910538, w_9=-0.079165743919001, w_10=-0.11858357370369, w_11=0.029537654173275, w_12=-0.039430094688785
Pattern: {0.4667, 0.4667, 1}
Forward propagating...
o_0=0.42336965891871, o_1=0.46681261718955, o_2=0.47238668385528, o_3=0.46923880487517
Back propagating...
e_0=0.14077149129128, e_1=-0.0036281503338587, e_2=-0.0025914934318792, e_3=-0.002815257681572
Descending Gradient...
w_0=-0.21828691198145, w_1=-0.11851111235637, w_2=-0.090300327397193, w_3=-0.095891095419484, w_4=-0.10977768369006, w_5=-0.027415242742418, w_6=-0.030405598457364, w_7=-0.094957694381343, w_8=0.037004149275705, w_9=-0.079254433978578, w_10=-0.12213154183806, w_11=0.028813915293439, w_12=-0.039639661438507
Pattern: {-0.2333, 0.2333, 1}
Forward propagating...
o_0=0.41064239971338, o_1=0.47240922253253, o_2=0.46951764352927, o_3=0.46552932793613
Back propagating...
e_0=0.14263350886241, e_1=-0.0042130460237454, e_2=-0.0032079955121886, e_3=-0.0034030691314723
Descending Gradient...
w_0=-0.22054236741781, w_1=-0.12018479821066, w_2=-0.093375111603894, w_3=-0.098303930329858, w_4=-0.11352187174241, w_5=-0.027680621087204, w_6=-0.031059444678234, w_7=-0.098836482228868, w_8=0.036396997865772, w_9=-0.079465229468972, w_10=-0.125920250257, w_11=0.028301489106551, w_12=-0.039967210318221
Pattern: {0, 0.2333, 0}
Forward propagating...
o_0=0.40931580805603, o_1=0.46984463218182, o_2=0.47068971300755, o_3=0.46624029273415
Back propagating...
e_0=-0.09896289325629, e_1=0.0029626432250047, e_2=0.0023022292053734, e_3=0.0024210226628508
Descending Gradient...
w_0=-0.23989078363039, w_1=-0.12982812271131, w_2=-0.10429406015933, w_3=-0.10855006720548, w_4=-0.11637317842514, w_5=-0.027919461597512, w_6=-0.031526948960748, w_7=-0.1019245011807, w_8=0.035850561596832, w_9=-0.079560951147443, w_10=-0.12890640886805, w_11=0.027840305538353, w_12=-0.040163160007197
Pattern: {-0.7, -0.7, 0}
Forward propagating...
o_0=0.40042793030022, o_1=0.48131852757729, o_2=0.48217574908441, o_3=0.46996609790303
Back propagating...
e_0=-0.096136900992837, e_1=0.0031159624126895, e_2=0.0025034414731012, e_3=0.0025995034261134
Descending Gradient...
w_0=-0.27412831589545, w_1=-0.14660479729745, w_2=-0.12223321825313, w_3=-0.12567828013276, w_4=-0.11839406101738, w_5=-0.028516123452344, w_6=-0.032329408210566, w_7=-0.10426561597956, w_8=0.035052097374331, w_9=-0.079953772238522, w_10=-0.13113903851842, w_11=0.027106801157275, w_12=-0.040657953896973
Pattern: {0.2333, -0.2333, 1}
Forward propagating...
o_0=0.3867248942574, o_1=0.4706576483402, o_2=0.48065098066991, o_3=0.47119953530586
Back propagating...
e_0=0.14544969049205, e_1=-0.0053125465219359, e_2=-0.0044380398387501, e_3=-0.0045548041945905
Descending Gradient...
w_0=-0.2794883990979, w_1=-0.14972382780118, w_2=-0.12614411667225, w_3=-0.12909990211751, w_4=-0.12114255099173, w_5=-0.029270017114816, w_6=-0.032834723542277, w_7=-0.10714927627031, w_8=0.034152285502564, w_9=-0.080126117148977, w_10=-0.13394549593781, w_11=0.026260685946051, w_12=-0.040917307129518
Pattern: {0.4667, -0.2333, 0}
Forward propagating...
o_0=0.38430431066374, o_1=0.46825711763504, o_2=0.48187869515808, o_3=0.47199343866275
Back propagating...
e_0=-0.090931975185917, e_1=0.0033899525495465, e_2=0.0028638667085448, e_3=0.0029256193416952
Descending Gradient...
w_0=-0.30022556963764, w_1=-0.15998237555979, w_2=-0.13733210702084, w_3=-0.13969023864296, w_4=-0.12302295027248, w_5=-0.029671655511439, w_6=-0.033427910628534, w_7=-0.10924339385799, w_8=0.033576353971727, w_9=-0.080398152086429, w_10=-0.13595932423046, w_11=0.025738124901633, w_12=-0.041270170762481
Pattern: {0.2333, -0.4667, 1}
Forward propagating...
o_0=0.37563783239746, o_1=0.4714449701285, o_2=0.4840333773248, o_3=0.47235476486292
Back propagating...
e_0=0.14643418862704, e_1=-0.0058376202949189, e_2=-0.0050224021830957, e_3=-0.0050982234441764
Descending Gradient...
w_0=-0.29326304011368, w_1=-0.157133827748, w_2=-0.1349974672311, w_3=-0.13711698633693, w_4=-0.12573689317677, w_5=-0.03027146551099, w_6=-0.033485005962628, w_7=-0.11200702006894, w_8=0.032852963468843, w_9=-0.080232791387837, w_10=-0.13866395879658, w_11=0.02505967224399, w_12=-0.041171363377903
Pattern: {-0.4667, 0, 1}
Forward propagating...
o_0=0.37893501730885, o_1=0.47212662792451, o_2=0.46820807362629, o_3=0.46248083228815
Back propagating...
e_0=0.14616346388791, e_1=-0.0057239623314301, e_2=-0.0049129810055401, e_3=-0.0049821612511488
Descending Gradient...
w_0=-0.26141815736172, w_1=-0.14249379363444, w_2=-0.12092018149457, w_3=-0.12297144418642, w_4=-0.12918113519862, w_5=-0.030343804197072, w_6=-0.033536391763313, w_7=-0.11535405533477, w_8=0.032603167457423, w_9=-0.080083966759105, w_10=-0.14197000812504, w_11=0.024855970416896, w_12=-0.041082436731783
Pattern: {0.4667, -0.4667, 0}
Forward propagating...
o_0=0.39060816373376, o_1=0.46812051591921, o_2=0.484314406258, o_3=0.47222947018894
Back propagating...
e_0=-0.092977799498948, e_1=0.0032987251095019, e_2=0.0028079569205115, e_3=0.0028495859404867
Descending Gradient...
w_0=-0.24902887779728, w_1=-0.13693460563957, w_2=-0.11613095968961, w_3=-0.11792415622539, w_4=-0.13170367612413, w_5=-0.03013949388804, w_6=-0.033852054110436, w_7=-0.11787499461293, w_8=0.032607683908735, w_9=-0.080179357454836, w_10=-0.14444677498107, w_11=0.024905371580236, w_12=-0.041235135558
Pattern: {0.2333, 0.2333, 1}
Forward propagating...
o_0=0.39617918472634, o_1=0.46340731602599, o_2=0.46780125436182, o_3=0.4630036129847
Back propagating...
e_0=0.14444676315069, e_1=-0.004918454552606, e_2=-0.0041762939395434, e_3=-0.0042351259988604
Descending Gradient...
w_0=-0.21260034263791, w_1=-0.12021724125063, w_2=-0.099995494091822, w_3=-0.10167770674648, w_4=-0.13483469250379, w_5=-0.030156422813158, w_6=-0.034336958426092, w_7=-0.12087469140269, w_8=0.032441241074099, w_9=-0.08043571672181, w_10=-0.14741701220129, w_11=0.024776923020523, w_12=-0.041545474108313
Pattern: {-0.4667, 0.7, 0}
Forward propagating...
o_0=0.41104623620335, o_1=0.46386397352397, o_2=0.45206764339391, o_3=0.45312252134245
Back propagating...
e_0=-0.099509043863834, e_1=0.0029750546375201, e_2=0.0024647527217018, e_3=0.0025072288869257
Descending Gradient...
w_0=-0.19722874367065, w_1=-0.11324937888603, w_2=-0.093345918371098, w_3=-0.094946615264562, w_4=-0.13713197268392, w_5=-0.030414638995647, w_6=-0.034408928117087, w_7=-0.12314308678718, w_8=0.032090140006264, w_9=-0.080364507853679, w_10=-0.14965146064428, w_11=0.024456547665514, w_12=-0.041517643264947
Pattern: {0.2333, 0, 1}
Forward propagating...
o_0=0.41633999052884, o_1=0.46400544684148, o_2=0.47111807326627, o_3=0.4640755722152
Back propagating...
e_0=0.14182996760467, e_1=-0.0039947286794869, e_2=-0.0032987684177001, e_3=-0.0033491897446933
Descending Gradient...
w_0=-0.1585740602693, w_1=-0.095461574196449, w_2=-0.075668034535314, w_3=-0.077370163840488, w_4=-0.13989860236495, w_5=-0.030810128345049, w_6=-0.034473700838982, w_7=-0.12576192710631, w_8=0.031639468577638, w_9=-0.080300419872361, w_10=-0.15224857244829, w_11=0.024031470801705, w_12=-0.041492595505917
Pattern: {0.4667, 0, 1}
Forward propagating...
o_0=0.43184480068734, o_1=0.4615068972174, o_2=0.47227950723315, o_3=0.46480005429237
Back propagating...
e_0=0.13939964438918, e_1=-0.003307109681143, e_2=-0.0026289188473575, e_3=-0.0026829798636822
Descending Gradient...
w_0=-0.099389907439976, w_1=-0.06819411793866, w_2=-0.048236709895004, w_3=-0.050212589159747, w_4=-0.14296731327208, w_5=-0.031436168674944, w_6=-0.034531996288688, w_7=-0.12857894419182, w_8=0.031019153917314, w_9=-0.080242740689175, w_10=-0.15505549454805, w_11=0.02342977595136, w_12=-0.04147005252279
Pattern: {-0.4667, -0.2333, 0}
Forward propagating...
o_0=0.45581345625713, o_1=0.46997622925835, o_2=0.46895624430365, o_3=0.4610005765164
Back propagating...
e_0=-0.11306341078627, e_1=0.0019206146577419, e_2=0.0013581958221652, e_3=0.0014106668727643
Descending Gradient...
w_0=-0.065910266781184, w_1=-0.052952402513623, w_2=-0.032827331404561, w_3=-0.034892174019272, w_4=-0.14539304552338, w_5=-0.032156466372483, w_6=-0.034662876088362, w_7=-0.1308765752999, w_8=0.030349943474737, w_9=-0.080246281164237, w_10=-0.1573348577351, w_11=0.022773037895883, w_12=-0.041507357839724
Pattern: {-0.7, 0, 0}
Forward propagating...
o_0=0.46957071066999, o_1=0.46931771997515, o_2=0.46204278505616, o_3=0.45678906566934
Back propagating...
e_0=-0.11695788258928, e_1=0.0015424699254065, e_2=0.00095432215498576, e_3=0.0010126088758009
Descending Gradient...
w_0=-0.056246219641394, w_1=-0.048840679819326, w_2=-0.028415811279181, w_3=-0.030453189727203, w_4=-0.14730627231261, w_5=-0.032993686866131, w_6=-0.034780667908069, w_7=-0.13277743692005, w_8=0.029630749612432, w_9=-0.080249467591792, w_10=-0.15920907805017, w_11=0.022057929058669, w_12=-0.041540932624964
Pattern: {0, 0, 1}
Forward propagating...
o_0=0.47348632895067, o_1=0.46323987980421, o_2=0.46685432257148, o_3=0.46028159202905
Back propagating...
e_0=0.13125829194473, e_1=-0.0015940231727097, e_2=-0.00092835500895917, e_3=-0.00099300257327101
Descending Gradient...
w_0=-0.024578376125256, w_1=-0.034499416202297, w_2=-0.013721705496983, w_3=-0.015885343137258, w_4=-0.14930713047815, w_5=-0.033747185310415, w_6=-0.034886680545805, w_7=-0.13465067450475, w_8=0.028983475136357, w_9=-0.080252335376592, w_10=-0.16106965178406, w_11=0.021414331105176, w_12=-0.04157114993168
Pattern: {-0.4667, -0.7, 0}
Forward propagating...
o_0=0.48630017145335, o_1=0.47274288846865, o_2=0.47701605238226, o_3=0.46456850769458
Back propagating...
e_0=-0.12148377146869, e_1=0.0010446660058851, e_2=0.00041586053992321, e_3=0.00048003018167089
Descending Gradient...
w_0=-0.017336976967753, w_1=-0.031642632026552, w_2=-0.010638209384543, w_3=-0.012650849729863, w_4=-0.15092508627609, w_5=-0.034510654394635, w_6=-0.035110063505488, w_7=-0.1362638127365, w_8=0.028366963737943, w_9=-0.080305859299053, w_10=-0.16266016286277, w_11=0.02079588768202, w_12=-0.04165714920498
Pattern: {-0.2333, -0.7, 1}
Forward propagating...
o_0=0.48920145842784, o_1=0.47046026395806, o_2=0.47834662107864, o_3=0.46546710619052
Back propagating...
e_0=0.12764007194126, e_1=-0.0010061926571366, e_2=-0.00033882879372895, e_3=-0.00040176321311714
Descending Gradient...
w_0=0.011517294863721, w_1=-0.018562849429387, w_2=0.0028217716139363, w_3=0.00065733894787065, w_4=-0.15255733020925, w_5=-0.035156696239724, w_6=-0.035187849568704, w_7=-0.13777493218397, w_8=0.027825937011947, w_9=-0.080312524302036, w_10=-0.16416193139591, w_11=0.020255691588763, w_12=-0.041685332557342
Pattern: {-0.2333, 0.7, 0}
Forward propagating...
o_0=0.5011460932255, o_1=0.45785355671793, o_2=0.45004583870191, o_3=0.45064441968049
Back propagating...
e_0=-0.12528586503611, e_1=0.00057728453476265, e_2=-8.7499823936699e-05, e_3=-2.0388204415718e-05
Descending Gradient...
w_0=0.015561113130728, w_1=-0.01682949640176, w_2=0.0050684876262259, w_3=0.0027543179677423, w_4=-0.1539253249555, w_5=-0.035761702984648, w_6=-0.035187139670089, w_7=-0.13915025215589, w_8=0.027342585357611, w_9=-0.080329241533152, w_10=-0.1655170910115, w_11=0.019770347504247, w_12=-0.041713195129509
Pattern: {0, 0.7, 0}
Forward propagating...
o_0=0.50285661618459, o_1=0.45547914234836, o_2=0.45130961195936, o_3=0.4514741405687
Back propagating...
e_0=-0.12571005060742, e_1=0.00052471579298695, e_2=-0.0001577794098408, e_3=-8.5746038174616e-05
Descending Gradient...
w_0=-0.0027987092852629, w_1=-0.025289682233061, w_2=-0.0028379449405428, w_3=-0.0052904973996687, w_4=-0.15506469496336, w_5=-0.036306209055079, w_6=-0.035122223076696, w_7=-0.14041565152733, w_8=0.02690756886871, w_9=-0.080363615018863, w_10=-0.16675174022222, w_11=0.019333537828183, w_12=-0.041748775334136
Pattern: {0.7, 0.4667, 1}
Forward propagating...
o_0=0.49551847218727, o_1=0.45094070548825, o_2=0.46031215449949, o_3=0.45693139000493
Back propagating...
e_0=0.1261102499, e_1=-0.00078964601200965, e_2=-8.8909758683625e-05, e_3=-0.00016555892062748
Descending Gradient...
w_0=0.0027467442728449, w_1=-0.022951906595872, w_2=0.00020502989565428, w_3=-0.0024466781687203, w_4=-0.15622831602253, w_5=-0.036892996154938, w_6=-0.035128290506557, w_7=-0.1415700701694, w_8=0.026505162583259, w_9=-0.080401812638269, w_10=-0.16789189732297, w_11=0.018920128151949, w_12=-0.041794319129245
Pattern: {-0.2333, -0.2333, 1}
Forward propagating...
o_0=0.49776034097321, o_1=0.46519991907862, o_2=0.46779564879412, o_3=0.4594504145613
Back propagating...
e_0=0.12555739548613, e_1=-0.0007169554343687, e_2=6.4090563171092e-06, e_3=-7.6294517617786e-05
Descending Gradient...
w_0=0.029710196685214, w_1=-0.010626282733924, w_2=0.01322236782264, w_3=0.010208053685417, w_4=-0.1574010421768, w_5=-0.037391833046815, w_6=-0.035104479695436, w_7=-0.14260792536241, w_8=0.026142735260607, w_9=-0.08043645216148, w_10=-0.16893139025423, w_11=0.018551174357756, w_12=-0.041832193630426
Pattern: {0.7, 0.7, 1}
Forward propagating...
o_0=0.50889817662071, o_1=0.44814995333704, o_2=0.45496896573639, o_3=0.45382491877136
Back propagating...
e_0=0.12273657160703, e_1=-0.00032255204089302, e_2=0.00040242618150747, e_3=0.00031055401894945
Descending Gradient...
w_0=0.075456203887578, w_1=0.010092546788556, w_2=0.034710204889291, w_3=0.031344972416113, w_4=-0.1585129423228, w_5=-0.037880298874513, w_6=-0.035122562590436, w_7=-0.14347157045436, w_8=0.025865847877455, w_9=-0.080418330525136, w_10=-0.16981258693905, w_11=0.018257158810303, w_12=-0.041828237814166
Pattern: {-0.7, 0.2333, 1}
Forward propagating...
o_0=0.52750061050689, o_1=0.46500958141926, o_2=0.45503697709776, o_3=0.45205993845325
Back propagating...
e_0=0.11776750384427, e_1=0.00029568830454432, e_2=0.0010136694833436, e_3=0.00091437098763656
Descending Gradient...
w_0=0.13723692354245, w_1=0.038323021450585, w_2=0.063427257815466, w_3=0.059684844118175, w_4=-0.1594619070009, w_5=-0.038356139936748, w_6=-0.035126764981682, w_7=-0.14407145887752, w_8=0.025492474720909, w_9=-0.080360635461596, w_10=-0.17044564903255, w_11=0.017880534371611, w_12=-0.041787346098035
Pattern: {-0.7, -0.4667, 0}
Forward propagating...
o_0=0.55291076881525, o_1=0.47097792208116, o_2=0.46893708581616, o_3=0.4592257800648
Back propagating...
e_0=-0.13667979116142, e_1=-0.0013050837889041, e_2=-0.002158941113258, e_3=-0.0020258655092166
Descending Gradient...
w_0=0.16892060777859, w_1=0.052465144940866, w_2=0.078056116431513, w_3=0.074206523999871, w_4=-0.16054436487425, w_5=-0.038624524128619, w_6=-0.035023957678055, w_7=-0.14498917315319, w_8=0.025420909166391, w_9=-0.080132383786336, w_10=-0.17136993138081, w_11=0.017789740901666, w_12=-0.041585086052716
Pattern: {-0.4667, 0.2333, 1}
Forward propagating...
o_0=0.56522423916059, o_1=0.46239877771686, o_2=0.45622536043696, o_3=0.45279743193788
Back propagating...
e_0=0.10684431657068, e_1=0.0013934751468277, e_2=0.0020689821193437, e_3=0.0019644708828781
Descending Gradient...
w_0=0.21613367899098, w_1=0.073838875325067, w_2=0.099752479382623, w_3=0.095742331521461, w_4=-0.16127471880957, w_5=-0.038979878500232, w_6=-0.034874538998233, w_7=-0.1454530441304, w_8=0.025187521225183, w_9=-0.079842485911125, w_10=-0.17185800308975, w_11=0.017547583530535, w_12=-0.041322847576958
Pattern: {0.2333, 0.7, 0}
Forward propagating...
o_0=0.58362305815029, o_1=0.45145814913533, o_2=0.45128836190852, o_3=0.45098538101763
Back propagating...
e_0=-0.14182459596354, e_1=-0.0025933664756506, e_2=-0.0035032695919673, e_3=-0.0033620326541313
Descending Gradient...
w_0=0.23380613878852, w_1=0.081870355491623, w_2=0.10807854286024, w_3=0.10393141488744, w_4=-0.1623858764846, w_5=-0.039405578104468, w_6=-0.035057749579661, w_7=-0.14648360018849, w_8=0.024834442338829, w_9=-0.080010728348452, w_10=-0.17288562334226, w_11=0.017192378508329, w_12=-0.041498681948907
Pattern: {-0.2333, -0.4667, 1}
Forward propagating...
o_0=0.59164340881369, o_1=0.46584549638798, o_2=0.47129747351387, o_3=0.46069894655344
Back propagating...
e_0=0.098659559093744, e_1=0.0020099008881598, e_2=0.0026569608089668, e_3=0.0025476191090167
Descending Gradient...
w_0=0.2669767754477, w_1=0.097141707115427, w_2=0.12370915015441, w_3=0.11925575203166, w_4=-0.1630341857367, w_5=-0.039870766976792, w_6=-0.035386792733234, w_7=-0.1469461324992, w_8=0.024408194273683, w_9=-0.080379147173716, w_10=-0.17336464822544, w_11=0.016768681069171, w_12=-0.041865003305342
Pattern: {0, -0.4667, 1}
Forward propagating...
o_0=0.60480335825775, o_1=0.46343559752612, o_2=0.47266897393202, o_3=0.46161908978091
Back propagating...
e_0=0.094458421731694, e_1=0.0022816953781009, e_2=0.0029126139725888, e_3=0.0027995835499127
Descending Gradient...
w_0=0.31336057224402, w_1=0.11854661772226, w_2=0.14559002064301, w_3=0.14067832232729, w_4=-0.16321836737242, w_5=-0.040289436961884, w_6=-0.035869283337217, w_7=-0.14685270413364, w_8=0.024024571015052, w_9=-0.080948604581129, w_10=-0.17330584349907, w_11=0.016387353373929, w_12=-0.042423341513614
Pattern: {0.4667, 0.2333, 1}
Forward propagating...
o_0=0.62207641928315, o_1=0.45254581990179, o_2=0.46144525110061, o_3=0.45622356563669
Back propagating...
e_0=0.088848831518398, e_1=0.0026094634733732, e_2=0.0032146475835526, e_3=0.0031008231531198
Descending Gradient...
w_0=0.37065453487642, w_1=0.14484746654709, w_2=0.1724576065725, w_3=0.16705224846901, w_4=-0.16292747473673, w_5=-0.040453118542937, w_6=-0.036196987010843, w_7=-0.14620605527751, w_8=0.023941858387051, w_9=-0.081329870223584, w_10=-0.17271027519355, w_11=0.016297410427184, w_12=-0.042799247043774
Pattern: {0, -0.2333, 1}
Forward propagating...
o_0=0.6445095157978, o_1=0.4614559443133, o_2=0.46823489025263, o_3=0.45940822857868
Back propagating...
e_0=0.081448913213459, e_1=0.0029318900445312, e_2=0.0034974479428951, e_3=0.0033791371566006
Descending Gradient...
w_0=0.43647266105794, w_1=0.17509562039248, w_2=0.20331244792348, w_3=0.19733698466088, w_4=-0.16215259060681, w_5=-0.040600431965885, w_6=-0.0366116220579, w_7=-0.14501201791699, w_8=0.02386741702185, w_9=-0.081815801357682, w_10=-0.17158291471617, w_11=0.016216461775114, w_12=-0.04327552374318

---Epoch 3---
Pattern: {0, -0.7, 1}
Forward propagating...
o_0=0.66972964306573, o_1=0.46592180152661, o_2=0.47807882225845, o_3=0.46473613248974
Back propagating...
e_0=0.07305311067736, e_1=0.0031829651187389, e_2=0.0037060144476138, e_3=0.0035860931673748
Descending Gradient...
w_0=0.50849326898984, w_1=0.20827544031677, w_2=0.23719370553449, w_3=0.23053457075502, w_4=-0.16089817599411, w_5=-0.040733014046539, w_6=-0.037374706827296, w_7=-0.14328883176418, w_8=0.02380041979317, w_9=-0.082707126148203, w_10=-0.16994072398223, w_11=0.016143607988251, w_12=-0.044143469185648
Pattern: {0.2333, -0.7, 1}
Forward propagating...
o_0=0.6956104174855, o_1=0.46400266497692, o_2=0.48005029513937, o_3=0.4662329783932
Back propagating...
e_0=0.064450404492868, e_1=0.0033384648956167, e_2=0.0038157233903735, e_3=0.0036975702647016
Descending Gradient...
w_0=0.58459063691481, w_1=0.24337068115124, w_2=0.27310123863166, w_3=0.26567095644768, w_4=-0.15918497148594, w_5=-0.040716036743601, w_6=-0.038470445069466, w_7=-0.14107021263335, w_8=0.023895908734078, w_9=-0.083976744574993, w_10=-0.16781567752537, w_11=0.016229002130056, w_12=-0.045377572441296
Pattern: {0.4667, 0.7, 0}
Forward propagating...
o_0=0.71862809623999, o_1=0.44889992027117, o_2=0.45296406155754, o_3=0.45214545222099
Back propagating...
e_0=-0.14530786263613, e_1=-0.0087485761105462, e_2=-0.0098331437859417, e_3=-0.0095626141417992
Descending Gradient...
w_0=0.62764939208595, w_1=0.26354137751065, w_2=0.29389965148283, w_3=0.28579615295007, w_4=-0.15917408824794, w_5=-0.041415275253345, w_6=-0.040528310060961, w_7=-0.14079425557813, w_8=0.023178751345038, w_9=-0.086323961272881, w_10=-0.16757659318901, w_11=0.015524854254185, w_12=-0.047659685603749
Pattern: {0.7, 0, 0}
Forward propagating...
o_0=0.73430830486879, o_1=0.45309711009256, o_2=0.46889792597981, o_3=0.46090268038908
Back propagating...
e_0=-0.14326326997203, e_1=-0.009355891609701, e_2=-0.010485526445526, e_3=-0.010173435699715
Descending Gradient...
w_0=0.64133119949488, w_1=0.27033537385294, w_2=0.30086244927106, w_3=0.29235350540422, w_4=-0.16080157436543, w_5=-0.043190686634304, w_6=-0.042380388553306, w_7=-0.14238086135641, w_8=0.021248832705325, w_9=-0.088436456300981, w_10=-0.16914176853373, w_11=0.013644875292685, w_12=-0.049713587449957
Pattern: {0, 0.4667, 0}
Forward propagating...
o_0=0.73752531400988, o_1=0.45497715515211, o_2=0.45421507822973, o_3=0.45206192655574
Back propagating...
e_0=-0.14277142266803, e_1=-0.0095708048693649, e_2=-0.01064859609201, e_3=-0.010339011124178
Descending Gradient...
w_0=0.62865982719601, w_1=0.26508236680955, w_2=0.29578040402015, w_3=0.28696035584499, w_4=-0.16394120272331, w_5=-0.044788556877166, w_6=-0.04482893075711, w_7=-0.14567231087295, w_8=0.019511905929583, w_9=-0.091207399290595, w_10=-0.17235975329072, w_11=0.011952894227336, w_12=-0.052406511997584
Pattern: {0.2333, 0.4667, 0}
Forward propagating...
o_0=0.73345987515926, o_1=0.45132662072866, o_2=0.45420701617497, o_3=0.45164429470795
Back propagating...
e_0=-0.14338882872218, e_1=-0.0094124134688117, e_2=-0.010513964397365, e_3=-0.010190514570708
Descending Gradient...
w_0=0.59216254710064, w_1=0.24902950125496, w_2=0.27980912618615, w_3=0.27077339061866, w_4=-0.16841404060245, w_5=-0.046610925406641, w_6=-0.047801354079566, w_7=-0.15047455920739, w_8=0.017519412949982, w_9=-0.094559949738492, w_10=-0.17703927962188, w_11=0.010014058034886, w_12=-0.055662428891724
Pattern: {-0.4667, -0.4667, 0}
Forward propagating...
o_0=0.72426429234777, o_1=0.46895204111028, o_2=0.47140131343374, o_3=0.461144703281
Back propagating...
e_0=-0.14463958231933, e_1=-0.0089701588148898, e_2=-0.010084767777857, e_3=-0.0097320094743985
Descending Gradient...
w_0=0.53400306810893, w_1=0.22271184246887, w_2=0.25350290054658, w_3=0.24453266089248, w_4=-0.17400937248628, w_5=-0.047518441787358, w_6=-0.049743919773966, w_7=-0.1565614170695, w_8=0.016549817464678, w_9=-0.096753596945262, w_10=-0.18295395497794, w_11=0.0090639430054784, w_12=-0.057797916552652
Pattern: {-0.2333, 0, 1}
Forward propagating...
o_0=0.70347457184577, o_1=0.45935902810759, o_2=0.45998016795419, o_3=0.45386446163672
Back propagating...
e_0=0.061854640503134, e_1=0.0034211869706556, e_2=0.0038949692816945, e_3=0.0037491755568922
Descending Gradient...
w_0=0.49248409910443, w_1=0.20399830988186, w_2=0.23480638135825, w_3=0.22582888818347, w_4=-0.17844646346186, w_5=-0.048474885041049, w_6=-0.051492228898926, w_7=-0.16135796952111, w_8=0.015518159669556, w_9=-0.098727879431355, w_10=-0.18762105707594, w_11=0.0080557700139628, w_12=-0.059719855447487
Pattern: {0.7, 0.2333, 1}
Forward propagating...
o_0=0.68830744413188, o_1=0.44413620199275, o_2=0.45672641585413, o_3=0.45117739645979
Back propagating...
e_0=0.06687061646489, e_1=0.0033678013064358, e_2=0.0038960089143374, e_3=0.0037393330390067
Descending Gradient...
w_0=0.46681938488175, w_1=0.19235357133732, w_2=0.22332429006095, w_3=0.21427533210671, w_4=-0.18185048011126, w_5=-0.048923128309332, w_6=-0.052928208203552, w_7=-0.16499306516754, w_8=0.015066928745953, w_9=-0.10034566936489, w_10=-0.19116706568231, w_11=0.0076064826188772, w_12=-0.061296932833189
Pattern: {-0.7, 0.4667, 1}
Forward propagating...
o_0=0.67899532731356, o_1=0.45702978918652, o_2=0.44463514697085, o_3=0.44396169932143
Back propagating...
e_0=0.069966394430652, e_1=0.003339721556497, e_2=0.0038584034461352, e_3=0.0037009386285529
Descending Gradient...
w_0=0.45596526110669, w_1=0.18746923378418, w_2=0.21843457355576, w_3=0.20931305152681, w_4=-0.18432964382333, w_5=-0.049735663141457, w_6=-0.053947826168893, w_7=-0.16758943064626, w_8=0.014188166492558, w_9=-0.10148655484961, w_10=-0.19371080916805, w_11=0.0067487589813023, w_12=-0.06241403757018
Pattern: {-0.2333, 0.4667, 0}
Forward propagating...
o_0=0.67497257665688, o_1=0.45068490983369, o_2=0.445649767926, o_3=0.44413079386784
Back propagating...
e_0=-0.1480785869981, e_1=-0.0068725326626172, e_2=-0.0079908238849359, e_3=-0.007651949104279
Descending Gradient...
w_0=0.42028279698448, w_1=0.17139439267619, w_2=0.20248537081324, w_3=0.19333790343521, w_4=-0.18776358438015, w_5=-0.050186356163087, w_6=-0.055426779261587, w_7=-0.17132455375698, w_8=0.013723525826666, w_9=-0.10316598234961, w_10=-0.19733926939847, w_11=0.0062892176595399, w_12=-0.064044385646692
Pattern: {0.4667, -0.7, 0}
Forward propagating...
o_0=0.66476856808215, o_1=0.457009707118, o_2=0.4768406843192, o_3=0.46267630276611
Back propagating...
e_0=-0.14814455220834, e_1=-0.0063008593548233, e_2=-0.0074831870828484, e_3=-0.0071205893640658
Descending Gradient...
w_0=0.36224328263802, w_1=0.14507892345621, w_2=0.17576885215567, w_3=0.1669652497569, w_4=-0.19195678126838, w_5=-0.051106586818211, w_6=-0.055985981774045, w_7=-0.17599572229611, w_8=0.012694178630338, w_9=-0.10376077668196, w_10=-0.20185098674455, w_11=0.0052940741351171, w_12=-0.064639426718454
Pattern: {0.7, -0.7, 0}
Forward propagating...
o_0=0.64309284934461, o_1=0.45300383385974, o_2=0.47639823967505, o_3=0.46184990866599
Back propagating...
e_0=-0.14760552384142, e_1=-0.0053063158197175, e_2=-0.0064716611958048, e_3=-0.006125379239126
Descending Gradient...
w_0=0.28417675305396, w_1=0.10969347422341, w_2=0.13941815831209, w_3=0.13129983184808, w_4=-0.19665926373624, w_5=-0.052584818095738, w_6=-0.055839240347343, w_7=-0.1813323146906, w_8=0.010974987657157, w_9=-0.10350331308458, w_10=-0.20698347372288, w_11=0.0036480860063436, w_12=-0.064424604726247
Pattern: {-0.7, -0.2333, 0}
Forward propagating...
o_0=0.61260257806532, o_1=0.46336014734981, o_2=0.45887623678563, o_3=0.45152601137149
Back propagating...
e_0=-0.14538324778459, e_1=-0.0039654890795651, e_2=-0.0050329878534389, e_3=-0.004727345526633
Descending Gradient...
w_0=0.18847480806601, w_1=0.06605772936864, w_2=0.095027773266735, w_3=0.087713200081475, w_4=-0.20158545854624, w_5=-0.053429453833265, w_6=-0.055545272057914, w_7=-0.18701602072, w_8=0.010044256793341, w_9=-0.10306611153536, w_10=-0.21242999747053, w_11=0.0027457965174601, w_12=-0.064038259233772
Pattern: {0.7, -0.2333, 0}
Forward propagating...
o_0=0.57473223325938, o_1=0.44373250641992, o_2=0.4610938794242, o_3=0.45126328273253
Back propagating...
e_0=-0.14047323242154, e_1=-0.0022904570073804, e_2=-0.0033170086370384, e_3=-0.0030510726657912
Descending Gradient...
w_0=0.07776024190308, w_1=0.015877364585569, w_2=0.043741440879725, w_3=0.037391909391775, w_4=-0.20641986385153, w_5=-0.054470206980444, w_6=-0.05518718696396, w_7=-0.19271183265793, w_8=0.0088002654578685, w_9=-0.10253720497093, w_10=-0.21786580655993, w_11=0.0015599795759054, w_12=-0.063565980621281
Pattern: {-0.7, 0.7, 1}
Forward propagating...
o_0=0.52997821564041, o_1=0.44845335248672, o_2=0.43274800369156, o_3=0.43451483408522
Back propagating...
e_0=0.11708304060834, e_1=0.00045980314129646, e_2=0.0012571820843669, e_3=0.001075715581784
Descending Gradient...
w_0=-0.0013933355370984, w_1=-0.02009636435517, w_2=0.0064505458470597, w_3=0.0010057534147674, w_4=-0.21069036307657, w_5=-0.055463210697714, w_6=-0.054808584494592, w_7=-0.19761805653731, w_8=0.0075266684506087, w_9=-0.10190718425761, w_10=-0.22256978451358, w_11=0.00036096916973772, w_12=-0.063009154711272
Pattern: {-0.4667, 0.4667, 1}
Forward propagating...
o_0=0.4982194286126, o_1=0.44759693307766, o_2=0.43814575527926, o_3=0.4372957052916
Back propagating...
e_0=0.12544355198443, e_1=-0.00062331707209664, e_2=0.00019919896791203, e_3=3.1045259936138e-05
Descending Gradient...
w_0=-0.050678933635983, w_1=-0.042646794301879, w_2=-0.017492811712241, w_3=-0.022141999820159, w_4=-0.21464289286672, w_5=-0.056306006179686, w_6=-0.054518750135732, w_7=-0.20199879820937, w_8=0.0063641620663681, w_9=-0.10132389653791, w_10=-0.22679793175137, w_11=-0.00072067573980536, w_12=-0.062505475848271
Pattern: {0.7, -0.4667, 0}
Forward propagating...
o_0=0.47810305373125, o_1=0.44309432839252, o_2=0.46250650838981, o_3=0.45062862956255
Back propagating...
e_0=-0.11929652437068, e_1=0.0012554285890346, e_2=0.0005187743212484, e_3=0.00065392725260873
Descending Gradient...
w_0=-0.11591286368985, w_1=-0.072192613589395, w_2=-0.048697531831812, w_3=-0.052382702857122, w_4=-0.21798046967477, w_5=-0.056910732111304, w_6=-0.054360433204196, w_7=-0.205850680208, w_8=0.0053814561749045, w_9=-0.10084130718594, w_10=-0.23048882699618, w_11=-0.0016140500699496, w_12=-0.062105572745109
Pattern: {0.4667, 0.4667, 1}
Forward propagating...
o_0=0.45232382108524, o_1=0.43292901265515, o_2=0.43772460671459, o_3=0.43530796270516
Back propagating...
e_0=0.13567416689618, e_1=-0.0024046066711641, e_2=-0.001626125846702, e_3=-0.0017470017587664
Descending Gradient...
w_0=-0.15088042153149, w_1=-0.088504826402655, w_2=-0.066388893703884, w_3=-0.069263827683311, w_4=-0.22140509496947, w_5=-0.057651375688111, w_6=-0.054414338204164, w_7=-0.20960194602994, w_8=0.0043642111093724, w_9=-0.10053978653238, w_10=-0.23411635802429, w_11=-0.0025607689682222, w_12=-0.061888341953406
Pattern: {-0.2333, 0.2333, 1}
Forward propagating...
o_0=0.43783392659548, o_1=0.44506024726114, o_2=0.44174672773579, o_3=0.43832629638233
Back propagating...
e_0=0.13836895971683, e_1=-0.0030246161838672, e_2=-0.0022653678152644, e_3=-0.0023595369428342
Descending Gradient...
w_0=-0.15813665563853, w_1=-0.092408876335242, w_2=-0.071614413233103, w_3=-0.073842958138665, w_4=-0.22501656556687, w_5=-0.05819446738999, w_6=-0.054586340221382, w_7=-0.21337452463736, w_8=0.0035411798548713, w_9=-0.10036090724865, w_10=-0.23779405491459, w_11=-0.003316481982134, w_12=-0.061789168235407
Pattern: {0, 0.2333, 0}
Forward propagating...
o_0=0.43468737661323, o_1=0.44084051790639, o_2=0.44107787024769, o_3=0.43727974868818
Back propagating...
e_0=-0.10681758135647, e_1=0.0024331765788538, e_2=0.0018858613165358, e_3=0.0019409025738269
Descending Gradient...
w_0=-0.18336034307225, w_1=-0.10416318690474, w_2=-0.084562483285102, w_3=-0.086138279446414, w_4=-0.22784108320324, w_5=-0.058683249921681, w_6=-0.054641801520105, w_7=-0.21643981965364, w_8=0.0028004517258203, w_9=-0.10012292089039, w_10=-0.24076432416543, w_11=-0.0039966236946546, w_12=-0.061620669689375
Pattern: {-0.7, -0.7, 0}
Forward propagating...
o_0=0.42320752545227, o_1=0.46293970584023, o_2=0.46298929624967, o_3=0.45144544082736
Back propagating...
e_0=-0.10330619097376, e_1=0.0026753960676848, e_2=0.0021719907428157, e_3=0.0022036754934306
Descending Gradient...
w_0=-0.224140245183, w_1=-0.12311136050794, w_2=-0.10458593694691, w_3=-0.10536556268515, w_4=-0.22991495476413, w_5=-0.059450890218495, w_6=-0.055019452707248, w_7=-0.2188184867883, w_8=0.0018677275436795, w_9=-0.10017480203396, w_10=-0.24305192327985, w_11=-0.0048787014838684, w_12=-0.061738971245891
Pattern: {0.2333, -0.2333, 1}
Forward propagating...
o_0=0.40794049750373, o_1=0.44251806539789, o_2=0.4514009285146, o_3=0.4428048404978
Back propagating...
e_0=0.14299719975935, e_1=-0.0043429763789337, e_2=-0.0037035510955388, e_3=-0.0037174566975918
Descending Gradient...
w_0=-0.23581764712479, w_1=-0.12909091901673, w_2=-0.11131095821192, w_3=-0.11158914345957, w_4=-0.23254146003524, w_5=-0.060319079353738, w_6=-0.055182025907565, w_7=-0.22160740865122, w_8=0.00087706904739961, w_9=-0.10007028833081, w_10=-0.24576131740489, w_11=-0.0058243459574818, w_12=-0.061693668183435
Pattern: {0.4667, -0.2333, 0}
Forward propagating...
o_0=0.40326782629311, o_1=0.43836053596033, o_2=0.4506978036615, o_3=0.44174417333822
Back propagating...
e_0=-0.097043533779959, e_1=0.0030842626937515, e_2=0.0026742456697991, e_3=0.0026705003618942
Descending Gradient...
w_0=-0.26330992728389, w_1=-0.14191703138351, w_2=-0.12501750616891, w_3=-0.12469233888786, w_4=-0.23436556880783, w_5=-0.060848550130602, w_6=-0.055454264522979, w_7=-0.22364944533563, w_8=0.00020388873021441, w_9=-0.10008540876307, w_10=-0.24773243455411, w_11=-0.006457319542927, w_12=-0.06176192528075
Pattern: {0.2333, -0.4667, 1}
Forward propagating...
o_0=0.39200365795501, o_1=0.44455865009645, o_2=0.45589195023546, o_3=0.44511835227872
Back propagating...
e_0=0.14490789655852, e_1=-0.0050780134073422, e_2=-0.004493760875279, e_3=-0.0044628026815184
Descending Gradient...
w_0=-0.26269409752935, w_1=-0.1421870222092, w_2=-0.12579248920605, w_3=-0.12519751104736, w_4=-0.23689591904945, w_5=-0.061532396422167, w_6=-0.055284545226841, w_7=-0.22627368650477, w_8=-0.00058544257738773, w_9=-0.099732000467009, w_10=-0.25028743045766, w_11=-0.0072092008463074, w_12=-0.061458868416326
Pattern: {-0.4667, 0, 1}
Forward propagating...
o_0=0.39242207783114, o_1=0.44814246264164, o_2=0.44373914720282, o_3=0.43858102351521
Back propagating...
e_0=0.14486297557529, e_1=-0.0050940175348581, e_2=-0.004497988641545, e_3=-0.004465704906868
Descending Gradient...
w_0=-0.23678883002458, w_1=-0.13106914509383, w_2=-0.11524073362194, w_3=-0.11453368937389, w_4=-0.24006468733551, w_5=-0.06173181693746, w_6=-0.055131797860317, w_7=-0.22942265156926, w_8=-0.00092847877690307, w_9=-0.099413933000556, w_10=-0.25336842512957, w_11=-0.0075211687353436, w_12=-0.061186117238346
Pattern: {0.4667, -0.4667, 0}
Forward propagating...
o_0=0.40191258810061, o_1=0.43951148171828, o_2=0.45426333694777, o_3=0.44316594053393
Back propagating...
e_0=-0.096611289597312, e_1=0.0031193585099119, e_2=0.0027600993286553, e_3=0.0027305698883125
Descending Gradient...
w_0=-0.23038106494981, w_1=-0.12849386562229, w_2=-0.11342437278612, w_3=-0.11242884564637, w_4=-0.24237069105372, w_5=-0.061656529593323, w_6=-0.055249091038346, w_7=-0.2317737027448, w_8=-0.0010117871440473, w_9=-0.099353096493168, w_10=-0.25566347060383, w_11=-0.0075789273662729, w_12=-0.061163653647366
Pattern: {0.2333, 0.2333, 1}
Forward propagating...
o_0=0.40512454697137, o_1=0.43299430498303, o_2=0.43654676594613, o_3=0.43248952160191
Back propagating...
e_0=0.14336418015374, e_1=-0.0045226466223011, e_2=-0.0039997762105725, e_3=-0.0039561056536046
Descending Gradient...
w_0=-0.19952534485562, w_1=-0.1153128362275, w_2=-0.10083724342413, w_3=-0.099683872795935, w_4=-0.24523755755902, w_5=-0.061773419338572, w_6=-0.055539303253544, w_7=-0.23458960963963, w_8=-0.0012500655377142, w_9=-0.099461644499757, w_10=-0.25842133002004, w_11=-0.0077924280376819, w_12=-0.061304954319057
Pattern: {-0.4667, 0.7, 0}
Forward propagating...
o_0=0.41698516759532, o_1=0.43652300873946, o_2=0.42467049776076, o_3=0.42612030484797
Back propagating...
e_0=-0.10137265429533, e_1=0.0028752909609831, e_2=0.0024975288799676, e_3=0.0024711482942767
Descending Gradient...
w_0=-0.18949541127254, w_1=-0.11119392158215, w_2=-0.097042572721142, w_3=-0.095772862842067, w_4=-0.24731456149562, w_5=-0.062113452310307, w_6=-0.055448271104502, w_7=-0.23668685829098, w_8=-0.0016684955194636, w_9=-0.09925339041789, w_10=-0.26047095254313, w_11=-0.0081864035010143, w_12=-0.06112940925753
Pattern: {0.2333, 0, 1}
Forward propagating...
o_0=0.420117198337, o_1=0.43491989628594, o_2=0.44100702072811, o_3=0.43477853519984
Back propagating...
e_0=0.14127031632816, e_1=-0.0038605684469567, e_2=-0.0033795982462418, e_3=-0.0033249117936524
Descending Gradient...
w_0=-0.15574616569033, w_1=-0.096734675919332, w_2=-0.082724658857246, w_3=-0.081504226173521, w_4=-0.24985946451677, w_5=-0.062577099343136, w_6=-0.055366342170364, w_7=-0.23916581177029, w_8=-0.0021830630504365, w_9=-0.09906596174421, w_10=-0.26289747237781, w_11=-0.0086767292542687, w_12=-0.060971418702156
Pattern: {0.4667, 0, 1}
Forward propagating...
o_0=0.43311042793531, o_1=0.43068321560311, o_2=0.44024084781121, o_3=0.43365677914576
Back propagating...
e_0=0.13918600727397, e_1=-0.0033013357314323, e_2=-0.0028374100384899, e_3=-0.0027861311215316
Descending Gradient...
w_0=-0.1010142933934, w_1=-0.073230966316347, w_2=-0.059115347356734, w_3=-0.058099635938926, w_4=-0.25272761098881, w_5=-0.063264010015208, w_6=-0.05529260612964, w_7=-0.24189341665841, w_8=-0.0028779121996807, w_9=-0.098897275937898, w_10=-0.26556891317528, w_11=-0.0093455727262211, w_12=-0.060829227202319
Pattern: {-0.4667, -0.2333, 0}
Forward propagating...
o_0=0.45372529751438, o_1=0.44761728624829, o_2=0.44584389127771, o_3=0.43855812957701
Back propagating...
e_0=-0.11245974057932, e_1=0.0020362859817188, e_2=0.0016425260600237, e_3=0.0016088014612955
Descending Gradient...
w_0=-0.071436062927541, w_1=-0.060886939354464, w_2=-0.046641377467867, w_3=-0.045666528086998, w_4=-0.25495259276684, w_5=-0.064048538186914, w_6=-0.055309380158906, w_7=-0.2440608189972, w_8=-0.0036374256436377, w_9=-0.098812518944933, w_10=-0.26769166963728, w_11=-0.010078926688326, w_12=-0.060766938194127
Pattern: {-0.7, 0, 0}
Forward propagating...
o_0=0.46528458600626, o_1=0.44766276114608, o_2=0.43991313001232, o_3=0.43520726827011
Back propagating...
e_0=-0.11576040414443, e_1=0.0017427675770109, e_2=0.0013303126430287, e_3=0.0012994012129048
Descending Gradient...
w_0=-0.065073726233545, w_1=-0.058846098965139, w_2=-0.044326595868653, w_3=-0.043293190641032, w_4=-0.2566500920411, w_5=-0.064968102569634, w_6=-0.055324476785247, w_7=-0.24577867638959, w_8=-0.0044839510419701, w_9=-0.098736237651264, w_10=-0.26937475524082, w_11=-0.010898121902801, w_12=-0.060710878086754
Pattern: {0, 0, 1}
Forward propagating...
o_0=0.46780870997632, o_1=0.43618736734606, o_2=0.43886278196328, o_3=0.43306059814576
Back propagating...
e_0=0.13249632376645, e_1=-0.001917473595777, e_2=-0.0014463254734087, e_3=-0.0014083439580273
Descending Gradient...
w_0=-0.03616076654982, w_1=-0.046895528651569, w_2=-0.032067444010951, w_3=-0.031115872925741, w_4=-0.25851339926719, w_5=-0.065795710514082, w_6=-0.055338063748953, w_7=-0.24757785500059, w_8=-0.0052458239004692, w_9=-0.098667584486963, w_10=-0.27113599247667, w_11=-0.011635397595829, w_12=-0.060660423990118
Pattern: {-0.4667, -0.7, 0}
Forward propagating...
o_0=0.47854995447647, o_1=0.4528728318706, o_2=0.45609776805672, o_3=0.44441977685017
Back propagating...
e_0=-0.1194173056541, e_1=0.0013875966820533, e_2=0.00094997111736793, e_3=0.00091746480298049
Descending Gradient...
w_0=-0.031037131323935, w_1=-0.045604164711895, w_2=-0.030565751489852, w_3=-0.029443784139876, w_4=-0.25994754635131, w_5=-0.0666538861541, w_6=-0.05552027260984, w_7=-0.24903087080495, w_8=-0.0060090959892016, w_9=-0.098722168100969, w_10=-0.2725605496484, w_11=-0.012373877363675, w_12=-0.060727404741511
Pattern: {-0.2333, -0.7, 1}
Forward propagating...
o_0=0.4803892278688, o_1=0.44879687353439, o_2=0.45548730008662, o_3=0.44345183062481
Back propagating...
e_0=0.12970285988352, e_1=-0.0014632399597694, e_2=-0.00098326123146246, e_3=-0.00094252393546389
Descending Gradient...
w_0=-0.0037278591410219, w_1=-0.034255145515454, w_2=-0.018875577265037, w_3=-0.017873434368389, w_4=-0.26149434571997, w_5=-0.067366503800659, w_6=-0.055505013689567, w_7=-0.25051065574438, w_8=-0.0066558967711333, w_9=-0.09865084385272, w_10=-0.27400759279167, w_11=-0.013000028258761, w_12=-0.06067222823567
Pattern: {-0.2333, 0.7, 0}
Forward propagating...
o_0=0.49151797399594, o_1=0.42931873104149, o_2=0.4211599673711, o_3=0.42227401693818
Back propagating...
e_0=-0.12284413135379, e_1=0.001030988178799, e_2=0.00056527567699395, e_3=0.00053564700805579
Descending Gradient...
w_0=-0.00064723716331309, w_1=-0.03327040339168, w_2=-0.017408400774425, w_3=-0.016538049414758, w_4=-0.26270604222049, w_5=-0.068049952352432, w_6=-0.055364984609418, w_7=-0.25174353894639, w_8=-0.0072610962675743, w_9=-0.098517405758864, w_10=-0.2752161933942, w_11=-0.013585433192561, w_12=-0.060556952621927
Pattern: {0, 0.7, 0}
Forward propagating...
o_0=0.49273028094623, o_1=0.42520023861014, o_2=0.42050376738841, o_3=0.42125927985069
Back propagating...
e_0=-0.12315653002503, e_1=0.0010014415106331, e_2=0.00052244049037803, e_3=0.0004965640226611
Descending Gradient...
w_0=-0.019427070137756, w_1=-0.041548218022066, w_2=-0.025150804282326, w_3=-0.024415348407261, w_4=-0.26362131680659, w_5=-0.068665056049027, w_6=-0.055116281852231, w_7=-0.25276170674238, w_8=-0.0078057758143711, w_9=-0.098333312514323, w_10=-0.27621703523252, w_11=-0.01411229763298, w_12=-0.060392375476782
Pattern: {0.7, 0.4667, 1}
Forward propagating...
o_0=0.4855759643731, o_1=0.4164388470796, o_2=0.42455113656834, o_3=0.42207019802086
Back propagating...
e_0=0.12849898154379, e_1=-0.0012974472101497, e_2=-0.00078956576196067, e_3=-0.00076528357077441
Descending Gradient...
w_0=-0.013841598044592, w_1=-0.039633656837538, w_2=-0.022571949423537, w_3=-0.022013689148022, w_4=-0.26467211719585, w_5=-0.069377586659206, w_6=-0.054998415128034, w_7=-0.25381623176712, w_8=-0.0083927092123285, w_9=-0.098232114403929, w_10=-0.27725171751188, w_11=-0.014680222866777, w_12=-0.060306758668586
Pattern: {-0.2333, -0.2333, 1}
Forward propagating...
o_0=0.48727296046491, o_1=0.44135733555981, o_2=0.44301352433247, o_3=0.43542338129961
Back propagating...
e_0=0.12809870962161, e_1=-0.0012517953942686, e_2=-0.0007134695753685, e_3=-0.00069322181159821
Descending Gradient...
w_0=0.013602601023038, w_1=-0.028016523367196, w_2=-0.010319824408541, w_3=-0.010091190490084, w_4=-0.26583690174019, w_5=-0.069967756531908, w_6=-0.054841227399797, w_7=-0.25489016146507, w_8=-0.0088918200914017, w_9=-0.098111906925487, w_10=-0.27830424538035, w_11=-0.015163053063682, w_12=-0.060201401027696
Pattern: {0.7, 0.7, 1}
Forward propagating...
o_0=0.49837705167459, o_1=0.41260587185209, o_2=0.41829104617183, o_3=0.41798288610953
Back propagating...
e_0=0.12540441582594, e_1=-0.0008515145557203, e_2=-0.00031489767507673, e_3=-0.00030785732343353
Descending Gradient...
w_0=0.060248152953443, w_1=-0.0085061485368441, w_2=0.0098868083557742, w_3=0.0098120157421766, w_4=-0.26703422287734, w_5=-0.070603219950416, w_6=-0.05480406897746, w_7=-0.25591180528637, w_8=-0.0093795948477646, w_9=-0.098042295160085, w_10=-0.27930539549356, w_11=-0.015635312763016, w_12=-0.060144291673015
Pattern: {-0.7, 0.2333, 1}
Forward propagating...
o_0=0.51623814278445, o_1=0.44265401166587, o_2=0.43236232762643, o_3=0.42986735993118
Back propagating...
e_0=0.12081290729268, e_1=-0.00025353363418692, e_2=0.00029314906152156, e_3=0.00029052395451944
Descending Gradient...
w_0=0.12337140846703, w_1=0.018411894473444, w_2=0.037213894059425, w_3=0.036813268314326, w_4=-0.26815618028677, w_5=-0.071144079156884, w_6=-0.054780977541806, w_7=-0.25677998363977, w_8=-0.0098545028885275, w_9=-0.097967676027915, w_10=-0.28015558890341, w_11=-0.016095935676846, w_12=-0.06008103188705
Pattern: {-0.7, -0.4667, 0}
Forward propagating...
o_0=0.54105920381084, o_1=0.45195146800648, o_2=0.44913647016195, o_3=0.4400772331834
Back propagating...
e_0=-0.13435265184777, e_1=-0.00061271080660421, e_2=-0.0012370114000928, e_3=-0.0012187304080748
Descending Gradient...
w_0=0.15667062435589, w_1=0.0320119794919, w_2=0.051248302926344, w_3=0.050767425552457, w_4=-0.2692731663464, w_5=-0.071555795368897, w_6=-0.054710153626365, w_7=-0.25777782115284, w_8=-0.010130386228703, w_9=-0.097799488995387, w_10=-0.28113404079369, w_11=-0.016361201824304, w_12=-0.059924561320428
Pattern: {-0.4667, 0.2333, 1}
Forward propagating...
o_0=0.5534373598768, o_1=0.43815778832978, o_2=0.43146742636705, o_3=0.42862124261584
Back propagating...
e_0=0.11036547744494, e_1=0.00086974246944079, e_2=0.0013874460388452, e_3=0.0013721960608629
Descending Gradient...
w_0=0.20595387720874, w_1=0.052714617371926, w_2=0.072212614896336, w_3=0.071604539981535, w_4=-0.27012624886792, w_5=-0.071997374001544, w_6=-0.054610902691797, w_7=-0.25843307185782, w_8=-0.010491997421468, w_9=-0.097591474712962, w_10=-0.2817745131843, w_11=-0.016712012039796, w_12=-0.059727714475793
Pattern: {0.2333, 0.7, 0}
Forward propagating...
o_0=0.57157295915798, o_1=0.41942095729003, o_2=0.41843653240072, o_3=0.41885321618405
Back propagating...
e_0=-0.13996524957463, e_1=-0.0017966470288193, e_2=-0.0024595746385143, e_3=-0.0024395429864482
Descending Gradient...
w_0=0.22581488610074, w_1=0.061073728645262, w_2=0.080831345273822, w_3=0.080098586353496, w_4=-0.27120843636733, w_5=-0.072468147377496, w_6=-0.054741666111717, w_7=-0.25945322305403, w_8=-0.010917865778511, w_9=-0.097705559751996, w_10=-0.28277785835847, w_11=-0.017127341675019, w_12=-0.059849396331461
Pattern: {-0.2333, -0.4667, 1}
Forward propagating...
o_0=0.58032018199778, o_1=0.44305966222125, o_2=0.44736896333559, o_3=0.43761421345219
Back propagating...
e_0=0.10221246081362, e_1=0.0015403845902325, e_2=0.0020426068039783, e_3=0.0020149044258416
Descending Gradient...
w_0=0.26157697474592, w_1=0.076522017004769, w_2=0.096590372074539, w_3=0.095570912575954, w_4=-0.27191283781351, w_5=-0.07295473346771, w_6=-0.05498516025009, w_7=-0.26001390293993, w_8=-0.011384541829139, w_9=-0.097975061091326, w_10=-0.2833282607407, w_11=-0.017583401857166, w_12=-0.060123472283282
Pattern: {0, -0.4667, 1}
Forward propagating...
o_0=0.59387560306879, o_1=0.43874640496111, o_2=0.44663182948234, o_3=0.43652713583781
Back propagating...
e_0=0.097952075655096, e_1=0.0018457494979803, e_2=0.0023383597533554, e_3=0.0023026271883104
Descending Gradient...
w_0=0.31090446776623, w_1=0.097946297712452, w_2=0.11842948627668, w_3=0.11697878550731, w_4=-0.27222379295292, w_5=-0.073392660948902, w_6=-0.055355051950499, w_7=-0.2601093018804, w_8=-0.011804550274704, w_9=-0.098408591983678, w_10=-0.28342066312675, w_11=-0.017993856021097, w_12=-0.060558201958959
Pattern: {0.4667, 0.2333, 1}
Forward propagating...
o_0=0.61122477064986, o_1=0.42082429937341, o_2=0.428352225242, o_3=0.42410442898663
Back propagating...
e_0=0.092384288567139, e_1=0.0022054503497792, e_2=0.0026790912673144, e_3=0.0026395006502081
Descending Gradient...
w_0=0.37146646198375, w_1=0.12403172221351, w_2=0.14500996678601, w_3=0.14310247368679, w_4=-0.27211769876719, w_5=-0.073606671038283, w_6=-0.055597911456712, w_7=-0.25972631995504, w_8=-0.011963749794183, w_9=-0.098689389188079, w_10=-0.28304191266041, w_11=-0.018147690151782, w_12=-0.060841694454271
Pattern: {0, -0.2333, 1}
Forward propagating...
o_0=0.63447094909803, o_1=0.43557347831335, o_2=0.44109922927273, o_3=0.43319004281902
Back propagating...
e_0=0.084772607001105, e_1=0.0025849798005101, e_2=0.0030305705576185, e_3=0.0029786441106743
Descending Gradient...
w_0=0.44080746300472, w_1=0.15397042664146, w_2=0.17547619727644, w_3=0.17304025666825, w_4=-0.27156984253493, w_5=-0.073799280118726, w_6=-0.055922023275109, w_7=-0.25885128637463, w_8=-0.012107029361714, w_9=-0.099065837291481, w_10=-0.28217977452134, w_11=-0.018286140869398, w_12=-0.061218448292481

This dataset can be visualized as a 7x7 grid of pixels that form the letter "Y":



After training, you could use your neural net to interpolate sub-pixel values. If you want to give your neural net some extra testing, see if you can reproduce these images. The interpolated image is shown below after 0, 100, 200, ... epochs. Even though the training set lies within the range (-0.7, -0.7) to (0.7, 0.7), I interpolated from (-1, -1) to (1, 1) just to see how this neural net generalizes in areas where no training was performed.



If you prefer sharp edges instead of fuzzy edges, try changing the output attribute from continuous to nominal. (Just replace "continuous" with "{0, 1}" in attribute 3 of the ARFF file.)

Now that you're getting correct results, don't forget to:
1- Initialize with small random weight values.
2- Randomly shuffle the dataset before each epoch.
3- Support nominal inputs by orthogonalizing each value.

Also note that you can do this same experiment with any supervised learning algorithm. Seeing how an algorithm interpolates an image can be a good way to gain an inutition for that algorithm's inductive bias.