def test(self, test_data, numClass):
numSample = test_data.shape[0]
self.flow = [test_data[:,1:]]
for i in range(0, len(self.architecture)):
self.flow.append(1 / ( 1 + np.exp(-np.dot(self.flow[i], self.architecture[i][0]) - np.matlib.repmat(self.architecture[i][1], numSample, 1))))
predictMat = getPrediction(self.flow[-1])
labelMat = oneOfK(test_data[:,0],numClass)
#Compute presicion
predictionAnalysis(predictMat, labelMat)
def predict(self, data, numClass):
self.flow = [data[:,1:]]
for i in range(0, len(self.architecture)):
self.flow.append(1 / ( 1 + np.exp(-np.dot(self.flow[-1], self.architecture[i][0]) - np.matlib.repmat(self.architecture[i][1], numSample, 1))))
return getPrediction(self.flow[-1])
