Artificial Intelligence Machine Learning Fundamentals

Question 1

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

Accepted Answer

Supervised learning

Answer

Supervised learning trains on labeled input-output pairs to learn a predictive mapping.

Question 2

What is the term for a model that performs well on training data but poorly on new data?

Accepted Answer

Overfitting

Answer

Overfitting occurs when a model memorizes training data instead of learning generalizable patterns.

Question 3

Which algorithm builds an ensemble of decision trees to improve prediction accuracy?

Accepted Answer

Random forest

Answer

Random forest combines many decision trees, using bagging and feature randomness to reduce variance.

Question 4

What does the 'bias-variance tradeoff' describe in machine learning?

Accepted Answer

The balance between underfitting and overfitting

Answer

The bias-variance tradeoff describes the tension between a model's error from wrong assumptions (bias) and sensitivity to fluctuations in training data (variance).

Question 5

Which metric is most appropriate when false negatives are more costly than false positives?

Accepted Answer

Recall

Answer

Recall (sensitivity) measures the proportion of actual positives correctly identified, minimizing false negatives.

Artificial Intelligence Practice Test

Artificial Intelligence Practice Test

Artificial Intelligence Machine Learning Fundamentals