Regression and Ensemble Methods Quiz

What is the primary goal of linear regression?

• To classify data into categories

• To predict a continuous outcome based on input features

• To reduce the dimensionality of data

• To cluster data into groups

In the linear regression equation y=mx+b, what does m represent?

• The intercept of the line

• The slope of the line

• The dependent variable

• The error term

What is the primary goal of logistic regression?

• To predict a continuous outcome

• To classify data into binary categories

• To reduce the dimensionality of data

• To cluster data into groups

What is the output of a logistic regression model?

• A continuous value between 0 and 1

• A discrete value (0 or 1)

• A probability value between 0 and 1

• A categorical label

Which metric measures the average absolute difference between predicted and actual values?

• Mean Squared Error (MSE)

• Root Mean Squared Error (RMSE)

• Mean Absolute Error (MAE)

• R-squared (R²)

What does a high R-squared (R²) score indicate?

• The model performs poorly

• The model explains a large proportion of the variance in the data

• The model is overfitting

• The model is underfitting

Which metric penalizes larger errors more heavily?

• Mean Absolute Error (MAE)

• Mean Squared Error (MSE)

• Root Mean Squared Error (RMSE)

• R-squared (R²)

What is the primary goal of a decision tree?

• To predict a continuous outcome

• To classify data into categories or predict values by splitting data into subsets

• To reduce the dimensionality of data

• To cluster data into groups

What is the criterion used to split nodes in a decision tree for classification?

• Mean Squared Error (MSE)

• Gini Impurity or Information Gain

• R-squared (R²)

• Mean Absolute Error (MAE)

What is a random forest?

• A single decision tree

• An ensemble of decision trees trained on random subsets of data and features

• A clustering algorithm

• A dimensionality reduction technique