ML Final Notes Quiz

What is the main goal of regression in machine learning?

• Classify data

• Predict numeric outputs

• Reduce dimensions

• Cluster data

When would you use polynomial regression?

• One feature only

• Multiple linear patterns

• Non-linear trends

• Binary classification

Which term refers to the value we are trying to predict in regression?

• Feature

• Attribute

• Target

• Variable

What does overfitting mean?

• Model is too simple

• Model memorizes training data

• Model has missing values

• None of the above

Which error metric penalizes large errors more?

• Mean Absolute Error

• Mean Squared Error

• R-squared

• Root Mean Absolute Error

Which metric uses the square root of the average squared errors?

• MAE

• MSE

• RMSE

• R²

What does R-squared represent?

• Data skewness

• Number of errors

• Variance explained by the model

• Feature correlation

Which metric keeps the same unit as the output variable?

• MSE

• MAE

• RMSE

• R²

Which formula calculates MSE?

• Average of squared differences

• Average of absolute errors

• Square root of error

• Total residual

What is the correct step to calculate MAE using Casio fx-991EX?

• Use ABS(A1 - B1), then divide sum by n

• (A1 - B1)^2

• SUM(A1 + B1)/n

• √(A1 - B1)