Artificial Intelligence Machine Learning

Question 1

Which type of machine learning uses labeled training data to learn a mapping from inputs to outputs?

Accepted Answer

Supervised learning

Answer

Unsupervised learning

Answer

Reinforcement learning

Answer

Semi-supervised learning

Question 2

What is the purpose of a validation set in machine learning?

Accepted Answer

To tune hyperparameters and detect overfitting

Answer

To train the model weights

Answer

To perform final evaluation of the model

Answer

To augment the training data

Question 3

Which metric is most appropriate when classes in a dataset are heavily imbalanced?

Accepted Answer

F1 Score

Answer

Accuracy

Answer

Mean Squared Error

Answer

R-squared

Question 4

What does regularization in machine learning primarily address?

Accepted Answer

Overfitting

Answer

Underfitting

Answer

Class imbalance

Answer

Data normalization

Question 5

In a decision tree, what does 'pruning' accomplish?

Accepted Answer

Removes branches to reduce overfitting

Answer

Adds more branches to improve accuracy

Answer

Normalizes feature values

Answer

Boosts minority class samples

Question 6

What is the 'bias-variance tradeoff' in machine learning?

Accepted Answer

The tension between underfitting (high bias) and overfitting (high variance)

Answer

The balance between model speed and accuracy

Answer

The tradeoff between precision and recall

Answer

The balance between training time and model size