Ensemble-Learning

We work on the EasyVisa Case Study and use ensemble learning techniques to provide machine learnig solutions and help in shortlisting the candidates having higher chances of VISA approval. Bagging, Boosting, and Stacking classifiers are provided.

Outline

1. Data Overview
2. Exploratory Data Analysis (EDA)
3. Data Preprocessing
4. Bagging Classifiers (Bagging & Random Forest)
5. Boosting Classifiers (AdaBoost, Gradient boosting, XGBoost)
6. Stacking Classifiers
7. Summary of Model Performances