Which of the following is a benefit of using Random Forests in financial applications?
Practice Questions
1 question
Q1
Which of the following is a benefit of using Random Forests in financial applications?
Higher interpretability than Decision Trees
Ability to handle large datasets with high dimensionality
Faster training times
Less computational power required
Random Forests can handle large datasets with many features, making them suitable for financial applications.
Questions & Step-by-step Solutions
1 item
Q
Q: Which of the following is a benefit of using Random Forests in financial applications?
Solution: Random Forests can handle large datasets with many features, making them suitable for financial applications.
Steps: 4
Step 1: Understand what Random Forests are. They are a type of machine learning model that uses many decision trees to make predictions.
Step 2: Recognize that financial applications often involve large datasets. This means there are many data points and features (like different financial indicators).
Step 3: Realize that Random Forests can process and analyze these large datasets effectively, which is important for making accurate financial predictions.
Step 4: Conclude that because Random Forests can handle many features and large amounts of data, they are beneficial for financial applications.
