Online Seminar #10 - Introduction to Random Forest & Boruta

Random Forest is one of the ensemble machine learning algorithms that builds a group of ‘decision tree’ based models to predict either categorical or numerical outputs based on the patterns inside the data.

It often used as ‘Variable Importance’ to find which variables are more important to predict the target output.

I have presented an online seminar to introduce the algorithm and demonstrate how you can use it inside Exploratory along with various methods like Boruta, EDARF, and SMOTE (adjusting imbalanced data).