#! /usr/bin/python from ann_trainer import ANN_Trainer ann = ANN_Trainer() ann.init([25, 50, 50, 25]) inputSamples = [[(float(j) / 100.0) for i in range(25)] for j in range(100)] desiredOutputs = [[(float(j) / 100.0) for i in range(25)] for j in range(100)] ann.addData(inputSamples, desiredOutputs) ann.train()
#! /usr/bin/python from ann_trainer import ANN_Trainer ann = ANN_Trainer() ann.init([25, 50, 50, 25]) inputSamples = [[(float(j) / 100.0) for i in range(25)] for j in range (100)] desiredOutputs = [[(float(j) / 100.0) for i in range(25)] for j in range (100)] ann.addData(inputSamples, desiredOutputs) ann.train()
#! /usr/bin/python from ann_trainer import ANN_Trainer ann = ANN_Trainer() ann.init([25, 30, 20, 3]) inputSamples = [] inputSamples.append([0, 0, 1, 0, 0, 0, 0.5, 0, 0.5, 0, 0, 1, 0, 1, 0, 0, 1, 1, 1, 0, 1, 0, 0, 0, 1]) inputSamples.append([1, 1, 1, 1, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1, 0]) inputSamples.append([1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 1, 1, 1, 1]) inputSamples.append([81.13636363636364, 42.5, 81.13636363636364, 42.5, 51.0, 52.15909090909091, 0.0, 54.09090909090909, 13.522727272727273, 17.0, 46.36363636363637, 0.0, 50.22727272727273, 46.36363636363637, 17.0, 48.29545454545455, 0.0, 50.22727272727273, 48.29545454545455, 31.166666666666668, 41.396103896103895, 44.70779220779221, 66.23376623376623, 62.922077922077925, 61.92857142857143]) desiredOutputs = [] desiredOutputs.append([1, 0, 0]) desiredOutputs.append([0, 1, 0])
