APPLICATION OF SUPERVISED LEARNING
LINEAR REGRESSION
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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decrease by 4 units
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increase by 4 units
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decrease by 3 units
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increase by 3 units
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Detailed explanation-1: -y = mx1 + mx2+ mx3+ b M= slope of the regression. X1=first independent variable of the regression. The x2=second independent variable of the regression. The x3=third independent variable of the regression.
Detailed explanation-2: -The adjusted R-squared compensates for the addition of variables and only increases if the new predictor enhances the model above what would be obtained by probability. Conversely, it will decrease when a predictor improves the model less than what is predicted by chance.
Detailed explanation-3: -Regularization. Handling Missing & Null Values. Deleting Missing Values. Imputing Missing Values. Imputing by Model-based Prediction. Categorical Feature Encoding. Label Encoding. One-Hot Encoding. Feature Engineering. Conclusion. 28-Nov-2022