Explain the difference between a decision tree and a random forest

Question

Accepted Answer

Decision tree is a single tree model while random forest is an ensemble of multiple decision trees.

Decision tree is a single tree model that makes decisions based on splitting data into branches at each node.
Random forest is an ensemble of multiple decision trees that make predictions by averaging the results of individual trees.
Decision tree tends to overfit the training data while random forest reduces overfitting by combining multiple trees.
Random forest is more robust and accurate compared to a single decision tree.
Example: Decision tree may predict a customer's likelihood to purchase based on age and income, while random forest may combine multiple decision trees to predict overall customer behavior.

Popular interview questions of Senior Data Science Analyst