Lecture-46: Feature Selection with “Correlation” Method by Python
In this video, I explain,
-Correlation Based Method.
-Remove the features which are highly correlated.
-If independent features are highly correlated with a dependent variable then need not remove those kinds of correlated features.
-If independent features are highly correlated among independent variables by 80% or 90% then drop those kinds of features and train the model with the remaining features.
-This is the way we can remove the features.
With the help of a correlation matrix, we suppose to choose the features.
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