Please Help

Complete the code for multiple linear regression code.

1. You are required to implement a multiple linear regression from scratch.

Problem:

For the years 1949 to 1966, the international production, the stock, the domestic consumption and the level of imports were noted in millions of French francs.

The goal is predict the levels of imports from the international production, the stock and the domestic consumption.

import numpy as np import pandas as pd

Read data from a file

df pd.read_csv("x13.txt",sep=r'\s+', header=None, skiprows=42)

df.head() 

	0	1	2	3	4	5	6
0	1	1949	1	149.3	4.2	108.1	15.9
1	2	1950	1	161.2	4.1	114.8	16.4
2	3	1951	1	171.5	3.1	123.2	19.0
3	4	1952	1	175.5	3.1	126.9	19.1
4	5	1953	1	180.8	1.1	132.1	18.8

Get X and Y

X = df.iloc[:, 3:6].values

y = df.iloc[:, 6].values

print(X[:5, :])

print(y[:5])

[[149.3 4.2 108.1] [161.2 4.1 114.8] [171.5 3.1 123.2] [175.5 3.1 126.9] [180.8 1.1 132.1]] [15.9 16.4 19. 19.1 18.8] 

Linear Regression

Complete the follwing code by computing b, sse, sst and r.

In [5]:

from numpy.linalg import inv

def multipleLinearRegression(X, y):

 n,m=X.shape

 X1 = np.hstack((np.ones((n,1)), X))

 # Begin your code

 b = None

 sse = 0.0

 sst = 0.0

 r = 0.0

 # End code

 return b, sse, sst, r

In [6]:

print(multipleLinearRegression(X,y))