Random Forest
(ป่าแบบสุ่ม)
Definition
Random Forest (ป่าแบบสุ่ม) Hard Skill
Random Forest is an ensemble learning method used for classification and regression by constructing multiple decision trees and aggregating their results to improve accuracy and control overfitting.
Expertise Level
Level 1
Basic
1. Understands the basic concept of decision trees.
2. Can explain what Random Forest is in general terms.
3. Knows simple applications of Random Forest models.
Level 2
Intermediate
1. Can build and tune Random Forest models using libraries like scikit-learn.
2. Understands parameters like the number of trees, max depth, and feature selection.
3. Can evaluate model performance using metrics such as accuracy and ROC AUC.
Level 3
Advanced
1. Can optimize Random Forest models for large and imbalanced datasets.
2. Understands techniques to reduce overfitting and improve generalization.
3. Able to interpret feature importance and explain model decisions in complex applications.
