Top 20 Random Forest Interview Questions & Answers
Last Updated on January 15, 2026 by Editorial Team
Author(s): Shahidullah Kawsar
Originally published on Towards AI.
Machine Learning Interview Preparation Part 07 Solution
A Random Forest is an ensemble learning algorithm that builds a “forest” of multiple Decision Trees to improve accuracy and prevent overfitting. During training, it uses two key techniques:
Bagging: Each tree is trained on a random subset of the data.
Feature Randomness: At each split, only a random selection of features is considered.
Let’s test your basic knowledge on Random Forest with 20 multiple-choice questions designed to assess your understanding of key concepts, algorithms, and advantages of using a Random Forest model. Each question follows with an explanation of the correct answer, enhancing your grasp of the subject while ensuring robust preparation for interviews.
Read the full blog for free on Medium.
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