This method enables feature scaling based on feature importance.
How to use:
- Before using please make sure you have the following libraries installed
- Numpy
- Pandas
- Sklearn
- Clone the github repository using the code below
! git clone git@github.com:NifulIslam/DTization.git
- Import DTization
from DTization import DTization- Create the DTization object. Pass classifier = False if the dataset is for regression. The default is True.
dtization= new DTization(classifier=True)- Now use the object as regular sklearn scalers with fit, transform, fit_transform functions. Just pass and extra dependent variable with it. [Note that once the dependent variable is passed to fit function, no need to pass it again for transform function]
dtization.fit_transform(X_train,y_train)
dtization.transform(X_test)