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)
def learningWithRestarts():
print "Learning With Restarts"
print "PenData"
data = []
for i in range(5):
data.append(testPenData()[1])
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)
