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To complete aspect variety, we should have ideally fetched the values from each column of the dataframe to examine the independence of each and every attribute with the class variable. Can it be a inbuilt features on the sklearn.preprocessing beacuse of which you fetch the values as Every single row.

Frequently, I recommend making numerous “views” about the inputs, in good shape a design to each and Evaluate the effectiveness in the ensuing versions. Even combine them.

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Each individual of such feature variety algo uses some predefined range like 3 in case of PCA.So how we arrive at realize that my details established cantain only 3 or any predefined variety of characteristics.it doesn't routinely decide on no capabilities its personal.

Can i use linear correlation coefficient amongst categorical and continuous variable for element selection.

The moment I bought the lessened version of my details as a result of utilizing PCA, how am i able to feed to my classifier?

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