What is a common evaluation metric for models using Decision Trees and Random Fo

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Question: What is a common evaluation metric for models using Decision Trees and Random Forests?

Options:

Correct Answer: Accuracy

Solution:

Accuracy is a common metric used to evaluate the performance of classification models like Decision Trees and Random Forests.

What is a common evaluation metric for models using Decision Trees and Random Forests?

What is a common evaluation metric for models using Decision Trees and Random Forests?

Evaluation Metrics – Metrics used to assess the performance of machine learning models, particularly in classification tasks.
Decision Trees – A type of model that makes decisions based on a series of questions, often used for classification and regression.
Random Forests – An ensemble learning method that combines multiple decision trees to improve accuracy and control overfitting.
Accuracy – The ratio of correctly predicted instances to the total instances, commonly used for evaluating classification models.