manojvenaram / 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:

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 1300cm3.

Step6:

Print the predicted output.

Program:

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:

Result

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