Machine Learning Quiz

What does a loss function measure in machine learning?

• Accuracy of a classification model

• The average of all predicted outputs

• The error for a single prediction

• The number of iterations during training

Which of the following best defines a cost function?

• It measures how fast the model trains

• It gives the maximum prediction error

• It calculates the error for one training sample

• It gives the average error across the dataset

In which type of task would you most likely use Cross-Entropy Loss?

• Regression

• Classification

• Clustering

• Dimensionality Reduction

If MAE is zero it indicates

• model has less errors

• model has more errors

• model has attained a calculating error

• model predictions are perfect

What does MSE do if it has large errors?

• weighs all errors equally

• punishes large errors more heavily

• punishes larger errors less

• becomes zero

What does MAE stand for?

• Maximum Approximation Error

• Mean Absolute Error

• Minimum Average Error

• Mean Angular Error

What is the main difference between MAE and MSE?

• MAE uses squared errors, MSE uses absolute errors

• MSE uses squared errors, MAE uses absolute errors

• MSE is always smaller than MAE

• There is no difference

What is the formula for MSE

• MSE = Σ(yi + ȳi)²

• MSE = (1/n) * Σ(yi - ȳi)

• MSE = (1/n) * Σ(yi * ȳi)

• MSE = (1/n) * Σ(yi- ȳi)²

What does MSE stands for?

• Maximum Squared Error
• Mean Squared Error
• Median Squared Error
• Mean Standard Error

Which of the following is NOT a typical loss function for classification?

• Hinge Loss
• Mean Squared Error (MSE)
• Cross-Entropy Loss
• Log Loss