def testNeuralNet(numIterations): trainData = df.labeled(df.flatPixelTrainData()) testData = df.flatPixelTestData().reshape(10,1000,900) net = NeuralNet(20) net.trainOnSet(trainData, numIterations) net.testOnSet(testData) net.displayClassMeans() return net
def testSingleCluster():
trainData = df.flatPixelTrainData()
unn = UnsupervisedNeuralNet(20)
np.random.shuffle(trainData)
unn.C = 1
unn.D = 900
unn.initializeSynapses()
unn.trainOnPoint(unn.synapses, trainData[0], 0, 0.01)
for p in trainData:
unn.classify(p)
def testUnsupervisedNeuralNet(): trainData = df.flatPixelTrainData() synthTrainData = sf.synthData(500,256,128) #testData = df.flatPixelTestData().reshape(10,1000,900) net = UnsupervisedNeuralNet(20) synapses = net.trainOnSetGrowing(trainData) #net.testOnSet(testData) net.displayClassMeans() return synapses