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