(self,inputs,targets,eta,nIterations)
Train the thing
Train the thing
Train the thing
def pcntrain(self,inputs,targets,eta,nIterations):
		""" Train the thing """	
		# Add the inputs that match the bias node
		inputs = np.concatenate((inputs,-np.ones((self.nData,1))),axis=1)
		# Training
		change = range(self.nData)

		for n in range(nIterations):
			
			self.activations = self.pcnfwd(inputs);
			self.weights -= eta*np.dot(np.transpose(inputs),self.activations-targets)
def pcntrain ( self , inputs , targets , eta , nIterations ) : # Add the inputs that match the bias node inputs = np . concatenate ( ( inputs , - np . ones ( ( self . nData , 1 ) ) ) , axis = 1 ) # Training change = range ( self . nData ) for n in range ( nIterations ) : self . activations = self . pcnfwd ( inputs ) self . weights -= eta * np . dot ( np . transpose ( inputs ) , self . activations - targets )