use strict;
 use AI::NNFlex::Backprop;
 use AI::NNFlex::Dataset;
 use Data::Dumper;
 
 my $n = 0.4;
 my $num_epochs = 100;
 
 my $network = AI::NNFlex::Backprop->new(learningrate=>.1,
				bias=>1,
				momentum=>0.6
 );
 $network->add_layer(nodes=>3,activationfunction=>'sigmoid');
 $network->add_layer(nodes=>3,activationfunction=>'sigmoid');
 $network->add_layer(nodes=>2,activationfunction=>'sigmoid');
 $network->add_layer(nodes=>3,activationfunction=>'sigmoid');
 $network->add_layer(nodes=>2,activationfunction=>'sigmoid');
 $network->init();
 
 my $train_set = AI::NNFlex::Dataset->new([
[5.5340,2.6382,4.2414],[-0.1521,0.2233],
[3.9251,4.1849,4.2922],[-0.1634,-0.1596],
[2.5816,2.6874,0.2919],[-0.6612,0.9220],
[6.2540,5.3605,1.0425],[0.0905,0.9889],
[1.8847,5.9803,1.9172],[-0.3500,0.9637],
[3.8622,2.3186,3.8525],[-0.5717,-0.6729],
[4.0471,0.5837,2.9998],[0.9751,0.8944],
[0.1537,1.6062,2.7142],[-0.9717,-0.5190],
[0.9319,5.4831,2.1002],[0.7892,0.9329],
[5.9391,4.3719,2.0253],[-0.2280,0.8969],
[3.8589,3.6751,2.4908],[-0.5647,-0.6714],
[5.4657,0.6344,4.7407],[-0.9880,0.9959],
[5.0981,2.1070,4.0408],[-0.9688,0.4978],
[5.8363,4.2850,3.2053],[0.6890,-0.0830],
[4.0277,1.2286,3.6781],[0.4710,0.6379],
[0.9807,6.1761,3.6123],[-0.9744,-0.8156],
[0.4826,5.8266,3.1986],[-0.0830,-0.6355],
[5.6870,2.4516,5.0457],[0.5794,-0.2372],
[1.4678,4.5695,1.8276],[0.9999,0.2152],
[6.1370,5.9400,5.7317],[-0.8629,0.7327],
[1.9392,0.4360,0.6980],[0.0682,0.6930],
[1.8824,0.6383,3.1576],[-0.5687,-0.3360],
[3.9325,5.2540,6.0191],[0.4814,0.4910],
[5.5595,3.1260,1.3106],[-0.5408,0.4331],
[3.8381,0.6247,0.4827],[-0.9730,-0.9168],
[4.7271,2.3532,1.3232],[0.8527,0.4970],
[4.4938,0.8037,4.3722],[-0.2426,0.7762],
[2.4121,2.9037,2.5048],[0.9994,-0.9895],
[1.2994,1.8898,3.2962],[0.2009,-0.7351],
[2.5134,1.6276,2.3341],[0.1908,0.1222],
[0.4626,4.4195,1.7705],[0.3611,0.8495],
[4.7609,4.2142,4.7134],[0.9011,-0.5189],
[3.3172,2.6081,0.8349],[0.4591,0.9921],
[2.8259,2.0912,1.1687],[-0.1960,0.9073],
[1.7875,2.6646,4.4482],[0.5008,0.5753],
[1.8996,2.8124,1.6491],[0.0778,-0.8366],
[1.9332,2.5489,0.5224],[-0.9576,0.4193],
[2.3862,4.7004,3.3423],[-0.8437,0.8100],
[0.3561,6.2829,1.3254],[0.9939,0.5661],
[0.7836,0.6747,1.2805],[0.3920,0.3887],
[5.3112,3.1028,1.5374],[-0.5026,0.7832],
[0.4225,5.5171,4.3372],[-0.7527,-1.0000],
[4.2945,3.1031,3.6578],[-0.9982,-0.7806],
[1.6475,1.3222,0.7899],[-0.5794,0.8940],
[2.6780,0.2432,2.5458],[-0.7286,0.9939],
[3.4686,1.6998,6.1486],[-0.9488,-0.3264],
[1.4655,1.0675,2.4023],[-0.9753,-0.4201],
[1.5529,1.2072,2.3019],[-0.9395,-0.3759],
[0.9813,2.1893,2.4928],[-0.5809,-0.8477],
[6.0636,4.0863,0.9625],[-0.9932,0.5278],
[5.6665,0.1528,3.9506],[-0.3384,0.0077],
[3.8016,5.0398,2.4865],[-0.9453,-0.8348],
[3.4299,2.2151,3.4295],[0.3431,-0.6003],
[5.6385,2.9992,2.5394],[-0.9836,0.9950],
[4.5908,2.2741,0.6373],[0.9388,-0.1083],
[3.2202,5.6121,1.0274],[-0.4213,-0.9617],
[3.3479,3.1709,2.5166],[0.3797,-0.6953],
[3.0010,4.5502,2.1642],[-0.2866,-0.8410],
[0.8316,3.0995,4.6960],[0.7158,0.7771],
[4.7967,5.0464,6.1339],[-0.2659,0.9950],
[0.4729,4.8273,1.9162],[0.8035,0.9999],
[0.0993,5.4944,5.8210],[-0.9134,0.2187],
[3.7814,5.7043,4.5935],[0.9983,0.9729],
[4.8448,2.6848,0.0043],[0.9492,-0.5522],
[2.7279,5.8683,1.4343],[-0.5694,-0.1372],
[5.8139,4.9424,1.3369],[-0.4557,0.8936],
[3.5784,0.2923,3.6134],[0.9323,0.9469],
[6.1181,0.7732,4.3905],[-0.9593,0.5780],
[0.4081,2.2920,4.2574],[0.6243,0.9900],
[5.9607,4.8815,1.9736],[0.2469,0.6259],
[3.3337,1.7212,0.0541],[-0.9224,0.0124],
[1.7599,3.7055,5.2455],[-0.9597,0.6154],
[0.4852,0.1804,2.4029],[0.0729,-0.5032],
[3.1002,4.0584,1.1857],[0.8822,-0.5422],
[3.3059,3.7911,4.0935],[-0.9810,-0.1333],
[0.5245,3.6482,5.8982],[-0.6021,-0.9200],
[1.5618,6.2071,1.9522],[-0.2920,0.9510],
[1.1077,0.7994,5.6519],[0.9568,0.5901],
[2.6820,4.5110,2.6853],[-0.4382,-0.1968],
[3.4817,4.5394,3.6957],[-0.7510,0.0410],
[6.0996,2.6882,0.2202],[0.4048,-0.9988],
[5.1756,2.8179,0.2649],[0.9193,-0.4986],
[4.1947,2.9655,4.0844],[-0.9691,-0.9593],
[6.1281,1.9555,4.5045],[0.0217,0.9454],
[3.1109,3.4934,1.9679],[0.7531,-0.7030],
[0.4649,0.2924,3.1929],[-0.7233,-0.9927],
[3.0673,1.5909,2.8188],[0.9298,0.2264],
[3.6315,5.8460,3.3502],[0.2583,0.7528],
[4.8192,5.8070,1.6455],[-0.2904,-0.8736],
[0.3948,3.2503,2.0376],[-0.5651,0.1797],
[6.0185,4.9840,3.6957],[0.8467,-0.8868],
[5.2400,1.8391,0.1164],[0.7909,-0.9898],
[4.4132,4.7653,4.4866],[0.8907,0.1260],
[1.1368,1.6150,4.5218],[0.8363,0.2837],
[1.2945,3.0269,4.1392],[0.8216,0.9165],
[2.1304,1.6573,2.3976],[-0.0977,-0.3464],
[1.6617,5.9765,1.6080],[0.1777,0.9358],
[3.8018,6.1612,4.4297],[0.9675,0.8748],
[1.0944,1.6855,0.0794],[0.2786,0.7836],
[0.1884,3.1365,0.5390],[-0.6611,-0.9409],
[2.0268,2.5542,1.7887],[0.0865,-0.6782],
[5.0352,0.0222,3.7997],[0.5377,0.3499],
[4.2030,2.6134,0.3378],[0.7650,0.3136],
[3.0253,0.9904,0.0346],[-0.7887,-0.4165],
[1.8271,1.6109,5.8611],[0.1253,0.8031],
[5.3684,2.0890,0.9048],[0.8736,-0.7200],
[3.6329,5.3425,2.8755],[-0.6560,-0.1270],
[4.9383,2.3600,0.3676],[0.9823,-0.5972],
[3.7106,0.6559,2.0575],[0.1403,0.5427],
[4.5009,5.0899,4.7424],[0.9809,0.5801],
[2.2240,3.4914,2.6341],[0.8797,-0.7249],
[0.4496,2.9264,0.0610],[-0.2911,-0.8232],
[1.9339,2.0413,5.2684],[0.1801,0.6158],
[0.0672,4.7777,5.0418],[-0.4456,-0.9469],
[3.3425,2.5392,6.2484],[-0.4226,0.6688],
[0.1650,3.0103,3.4485],[0.3341,0.9999],
[0.7814,4.1311,2.4528],[0.8830,0.8867],
[0.8563,2.1011,5.8930],[0.5434,0.6566],
[2.5677,1.4636,1.7530],[-0.4785,0.7968],
[6.2694,5.8874,4.7573],[-0.9343,-0.3307],
[5.7473,5.7283,4.6135],[-0.3720,-0.1177],
[1.0047,3.0440,5.7552],[-0.3700,0.0594],
[3.2436,4.7168,2.6994],[-0.9441,-0.5140],
[5.5943,1.6110,3.4079],[-0.9278,0.8390],
[5.5595,4.5983,4.3449],[0.9339,-0.9708],
[2.9657,4.5754,0.4729],[0.9872,-0.4897],
[1.2764,3.5884,0.6863],[-0.6684,-0.9898],
[2.5378,6.0620,5.8285],[0.9579,-0.9974],
[6.1402,4.3040,4.2097],[0.8694,-0.7192],
[5.1266,3.0453,3.1896],[-0.9338,0.4462],
[0.9140,0.1484,4.1952],[-0.8550,-0.9588],
[1.9633,0.0985,2.6169],[-0.9994,0.7302],
[3.2475,4.4928,2.0868],[-0.3915,-0.9819],
[0.2560,1.7329,2.7378],[-0.9999,-0.4774],
[4.2695,2.1248,2.8712],[0.1587,0.7475],
[4.8536,5.5924,1.6403],[-0.4618,-0.7231],
[5.5306,2.9369,4.7678],[0.6202,-0.5673],
[3.2925,5.2756,5.1452],[0.9115,0.6636],
[2.3980,5.4450,5.8478],[0.9020,-0.8628],
[5.2609,1.3351,5.4096],[-0.5318,0.0868],
[5.3450,3.2210,0.8752],[-0.0164,0.3164],
[2.8786,4.1886,6.2505],[0.6827,0.2893],
[4.6595,3.1193,1.6553],[-0.0094,0.9934],
[5.2902,0.3591,5.0356],[-0.9521,0.9945],
[2.4589,5.5967,1.5014],[-0.1319,-0.0731],
[1.1989,2.9440,4.2920],[0.8359,0.9699],
[1.4007,4.3817,5.7958],[-0.8350,-0.7973],
[2.8374,1.2346,0.4524],[-0.9824,0.4081],
[5.1153,0.8750,1.3218],[0.8567,-0.9752],
[1.2237,0.3685,4.9964],[0.3006,-0.5407],
[3.8471,2.3281,0.4555],[0.3406,0.4858],
[2.7967,1.3191,4.5017],[0.7224,-0.9931],
[5.2220,2.8499,4.7082],[0.2121,-0.6927],
[2.8660,2.2244,4.7338],[-0.3889,-0.5812],
[4.3218,0.3358,4.0157],[0.6827,0.9996],
[4.1818,3.5398,4.8490],[0.0042,-0.4842],
[1.2552,2.7262,5.8577],[-0.4025,0.5015],
[3.7468,0.6937,5.5425],[-0.5297,-0.7947],
[4.6458,0.4160,5.6699],[-0.9654,0.1304],
[3.8282,4.2185,3.8997],[-0.5810,-0.4100],
[4.2166,6.2005,0.3450],[-0.9729,-0.6875],
[4.1739,2.0613,3.3268],[-0.1367,0.3490],
[5.8329,5.7748,2.2769],[0.9683,-0.6036],
[2.3621,1.3956,2.3874],[-0.1376,0.1494],
[4.0352,0.2616,2.6201],[0.5922,0.4053],
[3.6630,2.5063,6.0631],[-0.3278,0.1928],
[2.8453,0.4987,2.3738],[-0.5357,0.9996],
[5.3606,0.4756,1.7312],[0.9592,-0.9999],
[2.0618,2.4722,4.6249],[0.2628,0.3174],
[5.2130,1.4297,3.1636],[-0.3723,0.8140],
[4.9403,5.7189,2.6434],[0.6715,-0.9609],
[1.1577,1.3957,0.2038],[0.3750,0.9040],
[4.9633,6.0459,5.8599],[-0.9172,0.7904],
[1.5738,0.6150,2.3907],[-0.9912,0.1385],
[1.0474,5.8627,1.5949],[0.7955,0.9919],
[3.4741,1.3534,3.6510],[0.8113,0.0405],
[4.9391,1.4557,3.7931],[-0.6912,0.9524],
[2.6547,4.1940,2.9256],[-0.3424,-0.2449],
[0.3649,1.6665,3.6264],[-0.5855,0.2139],
[5.2070,1.8115,0.6447],[0.9818,-0.9246],
[0.0335,2.9267,0.0999],[0.0815,-0.9890],
[4.3960,2.9445,1.2468],[0.7430,0.9791],
[3.0136,1.0945,4.5197],[0.7152,-0.8572],
[3.3508,5.2102,5.6917],[0.9933,0.2983],
[4.7758,1.6340,5.1324],[-0.8543,-0.4075],
[5.1793,5.2910,0.4546],[-0.9975,0.8439],
[0.9531,4.7461,2.4497],[0.9568,0.9992],
[1.3712,5.5541,2.7578],[-0.2554,0.7915],
[6.2456,0.1370,3.3101],[-0.2647,-0.9417],
[3.8731,3.8342,2.6510],[-0.8037,-0.8631],
[0.3462,0.9295,5.2808],[0.2700,0.9135],
[4.1782,5.5745,0.1970],[-0.5011,-0.0226],
[2.6387,2.8487,5.4376],[-0.9975,0.8047],
[5.7901,4.0368,1.1864],[-0.9998,0.8435],
[4.4426,5.5650,3.7703],[0.9361,0.1793],
[1.4368,2.9068,4.2683],[0.7263,0.8552],
[3.4556,0.4719,5.9739],[-0.4587,-0.9886],
[2.6051,0.1948,1.1812],[-0.7443,0.3351],
[4.1460,4.0784,1.2412],[-0.0408,0.3869],
[1.3771,0.8185,1.9272],[-0.8312,0.2009]
]);

my $epoch = 1;
my $err = 1;
while($err > .001 && $epoch < 100) {
	$err = $train_set->learn($network);
	#$outputsRef = $train_set->run($network);
	print "Error: $err\n";
	$epoch++;
}
foreach (@{$train_set->run($network)})
{
	foreach (@$_){print $_}
	print "\n";	
}