There are categorical features which have two different value in my dataframe next to numerical features. I've converted these categorical values to 0 or 1.
I will apply correalation elimination on features after calculating correlation coefficients. Depending on type of features, methods are given below:
Numeric - Numeric: Pearson
Numeric - Categoric: Cramer_V
Categoric - Categoric: Correlation Ratio
That's why I could not be sure what should be type of converted categorical features? Numerical or categorical ?
Another reason to I asked this question is that when I create dummy features for the categorical features which have only two different values, it creates features contains 0 and 1 like how I did manually. So after this process it's taking these features as numerical. But still each value from the feature represents a class and I think feature type should not be numerical.