CS CS Artificial Intelligence & Machine Learning 1

Question 1

Which type of machine learning algorithm learns from labeled training data to predict outcomes on new data?

Accepted Answer

Supervised Learning

Answer

Supervised learning uses labeled input-output pairs to train a model that can then predict labels for unseen inputs.

Question 2

What is the vanishing gradient problem in deep neural networks?

Accepted Answer

Gradients shrink exponentially as they propagate backward, halting learning in early layers

Answer

The vanishing gradient problem occurs when gradients become extremely small during backpropagation, preventing early layers from learning effectively.

Question 3

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

Accepted Answer

Removes branches to reduce overfitting and improve generalization

Answer

Pruning removes branches from a decision tree that have little predictive power, reducing model complexity and overfitting.

Question 4

Which distance metric is most commonly used in k-Nearest Neighbors (kNN) for continuous features?

Accepted Answer

Euclidean Distance

Answer

Euclidean distance measures the straight-line distance between two points in feature space and is the default metric for kNN with continuous data.

Question 5

What is the purpose of a confusion matrix in evaluating a classification model?

Accepted Answer

It shows the breakdown of true/false positives and negatives to assess classification performance

Answer

A confusion matrix summarizes prediction results by showing correct and incorrect classifications for each class, enabling computation of metrics like precision and recall.

(CS) Computer Science Practice Test

(CS) Computer Science Practice Test

CS CS Artificial Intelligence & Machine Learning 1