Di Bo's repositories
A-Randomized-Subspace-based-Approach-for-Dimensionality-Reduction-and-Important-Variable-Selection
A Randomized Subspace-based Approach for Dimensionality Reduction and Important Variable Selection
Language:R000
Language:Python000
Feature-selection-for-MONK-1-and-3
second paper (MONK)
Feature-subspace-selection-for-high-dimensioal-data
second paper code
Language:R000
Variable-Importance-in-Artificial-Neural-Network
1. Grid Search to fins the optimal hyperparameters. 2.
XGBoost-Regression
XGBoost Regression with cross validation and grid search for hyperparameter tuning
Language:Jupyter Notebook000