About this document

Random Forest Algorithm Explained by Abinet Arba is a document available to read on EtoBox.

The Random Forest Algorithm is an ensemble learning technique that improves accuracy and reduces errors by creating multiple decision trees using random subsets of data and features. It is effective for both classification and regression tasks, handling missing data well and providing insights into feature importance. While it offers high accuracy and reduces overfitting, it can be computationally expensive and harder to interpret than simpler models.

Author

Abinet Arba

Language

EN