gistfile1.txt

def train(self, train_data):
		print("In trainer...")
		u= np.zeros(self.weights.shape, dtype=np.int32)
		q=0
		for epoch in range(0,1):
			correct=0
			print("epoch: ",epoch+1)
			i=0
			for data in train_data:
				q += 1
				scores = np.zeros((4,))
				feature_vector = np.ones((len(data.featureVector),), dtype = np.float32)

				for index in data.featureVector:
					for i in range(0,4):
						scores[i] += self.weights[i][index]
				predicted = np.argmax(scores)

				if predicted!= data.label:
					for index in data.featureVector:
						self.weights[data.label][index]+=1
						self.weights[predicted][index]-=1
						u[data.label][index]+=q
						u[data.label][index]-=q

				if predicted==data.label:
					correct+=1
				i+=1
				if i%5000==0:
					print("States",i,": ", (correct/i))
			print("Accuracy: ", (correct/len(train_data)))
		u = u * (1/q)
		self.weights -= u