In this tutorial video, we learned how to do Polynomial Regression in Python using Sklearn. For this, We used PolynomialFeatures class in scikit-learn python package. Click "Show more" to learn more ๐:-
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How to do Polynomial Regression using Scikit learn Python package?
Polynomial regression is a special case of linear regression (linear_model). For this, we perform linear regression after creating some polynomial features using scikit learn package.
What is Polynomial regression? (Source: Wiki)
In statistics, polynomial regression is a form of regression analysis in which the relationship between the independent variable x and the dependent variable y is modeled as an nth degree polynomial in x. Polynomial regression fits a nonlinear relationship between the value of x and the corresponding conditional mean of y, denoted E(y |x).
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โTimeStamps:
Introduction (0:00)
What is Polynomial Regression (4:05)
How to do Polynomial Regression using sklearn (5:15)
Polynomial Features in sklearn (12:22)
Polynomial Regression modeling in Sklearn (17:00)
Polynomial Regression Curve (21:00)
R square metric in sklearn (27:35)
I used Anaconda jupyterlab for this code. It is an amazing platform for beginners. #fpritvik #regression
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