Society of Actuaries (SOA) PA Practice Exam

What is the role of Proportion of Features in Random Forest?

1. It determines the complexity of each decision tree

2. It specifies the fraction of features considered for splitting

3. It controls the training speed of the model

4. It affects the total number of trees in the forest

The correct answer is: It specifies the fraction of features considered for splitting

The Proportion of Features in a Random Forest model plays a crucial role in feature selection during the training of individual decision trees within the ensemble. Specifically, it specifies the fraction of features that are randomly selected at each split when constructing a decision tree. This approach fosters greater diversity among the trees in the forest, which enhances the model's ability to generalize from training data to unseen data. By limiting the number of features to be considered for splitting at each node, the model helps mitigate the risk of overfitting to the training data and improves overall robustness. This randomness contributes to the strength of the Random Forest algorithm, as it allows different trees to learn different patterns from the data. Other factors such as the complexity of trees, training speed, and the total number of trees do not directly relate to the proportion of features. While they are also important in understanding the functioning of a Random Forest, they operate separately from the specific function of selecting features for decision splits.