Quiz on Decision Trees in Machine Learning

What is the primary purpose of decision trees in machine learning?

• Data preprocessing

• Feature extraction

• Classification and regression tasks

• Data visualization

Which metric is commonly used to evaluate splits in decision trees for categorical features?

• Variance

• Root Mean Square

• Gini Impurity

• Mean Squared Error

What does the root node of a decision tree represent?

• A terminal decision

• A feature test

• The entire dataset

• A split condition

What is a disadvantage of decision trees?

• They can overfit the training data

• They are difficult to interpret

• They are non-parametric

• They handle categorical data poorly

Which of the following is NOT a measure used in computing information gain?

• Entropy

• Gini Index

• Standard Deviation

• Classification Error

How do decision trees handle numerical features?

• By using one-vs-all splits

• By evaluating threshold values

• By ignoring them

• By converting them to categorical

What is the main goal of maximizing information gain in decision trees?

• To reduce uncertainty or impurity

• To increase the number of features

• To enhance data visualization

• To minimize the tree depth

What is a leaf node in a decision tree?

• A node that splits the dataset

• A node that connects two branches

• A terminal node providing the output

• A node that represents a feature test

Which of the following applications can utilize decision trees?

• Database management

• Web development

• Customer segmentation

• Image processing

What is Gini Index used for in decision trees?

• To determine the number of features

• To evaluate the training time

• To measure the purity of a node

• To calculate the depth of the tree