Aim :- Make Bagging convenient according to the Base_Estimator_Model (Linear Regression, Decision Tree, SVMs, etc.) and according to their numbers too.
References :-
https://machinelearningmastery.com/implement-bagging-scratch-python/ <----- (Take Idea for Bagging Samples from here)
Most of the Implementation would be self-done. Still more resources would be tried to brough upon here.
Requirement :-
See KNN as Classifier and Regressor, in models.py, where the mode can be switched by changing the boolean value of the "classify" argument.
Aim :- Make Bagging convenient according to the Base_Estimator_Model (Linear Regression, Decision Tree, SVMs, etc.) and according to their numbers too.
References :-
https://machinelearningmastery.com/implement-bagging-scratch-python/ <----- (Take Idea for Bagging Samples from here)
Most of the Implementation would be self-done. Still more resources would be tried to brough upon here.
Requirement :-
See KNN as Classifier and Regressor, in models.py, where the mode can be switched by changing the boolean value of the "classify" argument.