Showing posts with label multiple linear regression. Show all posts
Showing posts with label multiple linear regression. Show all posts

Wednesday, February 26, 2020

Multiple Linear Regression

Multiple Linear Regression is a regression model where we have multiple independent variables.

We need to predict values for the dependent variable as a function of the independent variables.



Formula for Multiple Linear Regression:


<math xmlns="http://www.w3.org/1998/Math/MathML"><mi>y</mi><mo>=</mo><mo>&#xA0;</mo><msub><mi>b</mi><mi>o</mi></msub><mo>&#xA0;</mo><mo>+</mo><mo>&#x2009;</mo><msub><mi>b</mi><mn>1</mn></msub><msub><mi>x</mi><mn>1</mn></msub><mo>&#xA0;</mo><mo>+</mo><mo>&#xA0;</mo><msub><mi>b</mi><mn>2</mn></msub><msub><mi>x</mi><mn>2</mn></msub><mo>&#xA0;</mo><mo>+</mo><mo>&#x2009;</mo><mo>.</mo><mo>.</mo><mo>.</mo><mo>.</mo><mo>.</mo><mo>&#xA0;</mo><mo>+</mo><mo>&#x2009;</mo><msub><mi>b</mi><mi>n</mi></msub><msub><mi>x</mi><mi>n</mi></msub></math>

where

y is the dependent Variable
<math xmlns="http://www.w3.org/1998/Math/MathML"><msub><mi>x</mi><mn>1</mn></msub></math> onwards are the the independent Variable
<math xmlns="http://www.w3.org/1998/Math/MathML"><msub><mi>b</mi><mn>1</mn></msub></math> onwards is the coefficient (connector between dependent and Independent)
<math xmlns="http://www.w3.org/1998/Math/MathML"><msub><mi>b</mi><mn>0</mn></msub></math> is the Constant

Always encode the categorical data if any after data import.

Code Snippet:

from sklearn.linear_model import LinearRegression
multi_regressor = LinearRegression()
multi_regressor.fit(X_train, y_train)

# Prediction
y_pred = multi_regressor.predict(X_test)