/Multivariate-Linear-Regression

Implementation of Multivariate Linear Regression

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


Step1: import pandas as pd.

Step2

Read the csv file.

Step3

Get the value of X and y variables.

Step4

Create the linear regression model and fit.

Step5


Predict the CO2 emission of a car where the weight is 2300kg, and the volume is 1300cm cube.

Step6:

Print the predicted output.

Program:



Program:
#Reference Number: 21500582
#Developed By: PRANAVE B

import pandas as pd
from sklearn import linear_model

df=pd.read_csv("cars.csv")

x=df[['Weight', 'Volume']]
y=df['CO2']

regr=linear_model.LinearRegression()
regr.fit(x,y)

print('Coefficients: ', regr.coef_)
print('Intercept:', regr.intercept_)

predictedCO2=regr.predict([[3300, 1300]])
print('Predicted CO2 for the corresponding weight and volume',predictedCO2)

Output:

Insert your output


Result

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