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how to proceed with correlated options? should we change them to anything new? a mixture perhaps? how does it affect our modeling and prediction? appreciated if you immediate me into some resources to study and come across it out.
I've dilemma with regards to 4 automated feature selectors and feature magnitude. I observed you applied the same dataset. Pima dataset with exception of attribute named “pedi†all attributes are of similar magnitude. Do you'll want to do almost any scaling In case the function’s magnitude was of a number of orders relative to each other?
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Can i use linear correlation coefficient in between categorical and continual variable for feature range.
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