How do Decision Trees handle categorical variables?
Practice Questions
Q1
How do Decision Trees handle categorical variables?
By converting them to numerical values
By creating binary splits
By ignoring them
By using one-hot encoding
Questions & Step-by-Step Solutions
How do Decision Trees handle categorical variables?
Step 1: Identify the categorical variable in your dataset. A categorical variable is one that can take on a limited number of distinct categories or groups.
Step 2: For each category in the categorical variable, the Decision Tree will consider how to split the data. This means it looks at each category to see how well it separates the data into different groups.
Step 3: Create binary splits. This means that for each category, the Decision Tree will decide whether to include that category in one group or not. This results in two groups: one that includes the category and one that does not.
Step 4: Repeat the process. The Decision Tree will continue to create splits based on the remaining data until it reaches a stopping point, such as a maximum depth or a minimum number of samples in a group.
Decision Trees and Categorical Variables – Decision Trees can handle categorical variables by creating splits based on the distinct categories, often converting them into binary splits or using techniques like one-hot encoding.
