from NeuralNetUtil import buildExamplesFromCarData,buildExamplesFromPenData,buildExamplesFromXorData,buildExamplesFromExtraData from NeuralNet import buildNeuralNet import cPickle from math import pow, sqrt def average(argList): return sum(argList)/float(len(argList)) def stDeviation(argList): mean = average(argList) diffSq = [pow((val-mean),2) for val in argList] return sqrt(sum(diffSq)/len(argList)) penData = buildExamplesFromPenData() def testPenData(hiddenLayers = [24]): return buildNeuralNet(penData,maxItr = 200, hiddenLayerList = hiddenLayers) carData = buildExamplesFromCarData() def testCarData(hiddenLayers = [16]): return buildNeuralNet(carData,maxItr = 200,hiddenLayerList = hiddenLayers) xorData = buildExamplesFromXorData() def testXorData(hiddenLayers = [40]): return buildNeuralNet(xorData,maxItr = 200,hiddenLayerList = hiddenLayers) extraData = buildExamplesFromExtraData() def testExtraData(hiddenLayers = [40]): return buildNeuralNet(extraData,alpha = 10,maxItr = 200,hiddenLayerList = hiddenLayers)
def average(argList): return sum(argList) / float(len(argList)) def stDeviation(argList): mean = average(argList) diffSq = [pow((val - mean), 2) for val in argList] return sqrt(sum(diffSq) / len(argList)) penData = buildExamplesFromPenData() def testPenData(hiddenLayers=[24]): return buildNeuralNet(penData, maxItr=200, hiddenLayerList=hiddenLayers) carData = buildExamplesFromCarData() def testCarData(hiddenLayers=[16]): return buildNeuralNet(carData, maxItr=200, hiddenLayerList=hiddenLayers) xorData = buildExamplesFromXorData() def testXorData(hiddenLayers=[40]): return buildNeuralNet(xorData, maxItr=200, hiddenLayerList=hiddenLayers)