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EX 10 Implementation of Multivariate Linear Regression

Date: 08.11.2023

Aim

To write a python program to implement multivariate linear regression and predict the output.

Equipment’s required:

1. Hardware – PCs
2. Anaconda – Python 3.7 Installation / Moodle-Code Runner

Algorithm:

Step1

Import panda

Step2

Import linear model from sklearn

Step3

Read the file cars.csv

Step4

Assign the values for x and y as required

Step5

Create the linearRegression model and predict the output

Program:

import pandas as pd
from sklearn import linear_model
df=pd.read_csv("car.csv")
x=df[['Weight','Volume']]
y=df['CO2']
regr=linear_model.LinearRegression()
regr.fit(x,y)
print("Coefficient:", regr.coef_)
print("Intercept:", regr.intercept_)
predictedCO2=regr.predict([[3300,1300]])
print("Predictedd co2 for the corresponding weight and volume", predictedCO2)

Output:

Result

Thus the multivariate linear regression is implemented and predicted the output using python program.