Podcast
Questions and Answers
What is the primary purpose of a decision tree in artificial intelligence and machine learning?
What is the primary purpose of a decision tree in artificial intelligence and machine learning?
- To perform complex mathematical computations on large datasets
- To identify outliers in the dataset
- To visualize and analyze possible decision paths based on input features (correct)
- To automatically generate code for machine learning models
What are the nodes in a decision tree used to represent?
What are the nodes in a decision tree used to represent?
- Decision points based on features (correct)
- Data outliers
- Complex mathematical computations
- Random noise in the dataset
How does a decision tree handle categorical data?
How does a decision tree handle categorical data?
- By splitting the data based on categories (correct)
- By converting it into a continuous numerical form
- By removing categorical variables from the dataset
- By ignoring categorical data
Flashcards
Purpose of a Decision Tree
Purpose of a Decision Tree
To visualize and analyze possible decision paths based on input features, aiding in making informed choices.
Nodes in a Decision Tree
Nodes in a Decision Tree
Represent decision points based on the various features or attributes under consideration.
Decision Tree & Categorical Data
Decision Tree & Categorical Data
Decision trees handle categorical data by splitting the data based on distinct categories within those features.
