What is the role of the 'max_features' parameter in a Random Forest model?
Practice Questions
1 question
Q1
What is the role of the 'max_features' parameter in a Random Forest model?
It determines the maximum number of trees in the forest.
It specifies the maximum number of features to consider when looking for the best split.
It sets the maximum depth of each tree.
It controls the minimum number of samples required to split an internal node.
'max_features' specifies the maximum number of features to consider when looking for the best split, which helps to introduce randomness and reduce correlation among trees.
Questions & Step-by-step Solutions
1 item
Q
Q: What is the role of the 'max_features' parameter in a Random Forest model?
Solution: 'max_features' specifies the maximum number of features to consider when looking for the best split, which helps to introduce randomness and reduce correlation among trees.
Steps: 5
Step 1: Understand that a Random Forest model is made up of many decision trees.
Step 2: Each decision tree makes decisions based on features (variables) from the dataset.
Step 3: The 'max_features' parameter controls how many features each tree can use when making a decision.
Step 4: By limiting the number of features, 'max_features' helps to create diversity among the trees.
Step 5: This diversity reduces the chance that all trees will make the same mistakes, improving the overall model performance.
