least_squares.py
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			# -- coding: utf-8 --
			"""Exercise 3.

			Least Square
			"""

			import numpy as np

			def compute_loss(y, tx, w):
			"""Calculate the loss.

			You can calculate the loss using mse or mae.
			"""
			# ***************************************************
			# INSERT YOUR CODE HERE
			# TODO: compute loss by MSE
			# ***************************************************
			N = tx.shape[0]
			w0Array = np.array([w[0]]*N)
			w1Array = np.array([w[1]]*N)
			heights = tx[:,1]
			costMSE = (1/(2N))np.sum((y - tx@w)**2)
			return costMSE

			def least_squares(y, tx):
			"""calculate the least squares."""
			wStar = ((np.linalg.inv((tx.T)@tx))@(tx.T))@y
			#mse = compute_loss(y, tx, wStar)
			return wStar

ml2017/Vikalp/ex04/template/least_squares.pyb96a75e22936master