Artificial Intelligence Machine Learning 3

Question 1

What is the primary goal of unsupervised learning?

Accepted Answer

Discover hidden structure in unlabeled data

Answer

Unsupervised learning finds patterns, clusters, or structure in data without predefined labels.

Question 2

Which algorithm minimizes a cost function by iteratively updating model parameters using the gradient?

Accepted Answer

Gradient Descent

Answer

Gradient descent updates parameters by moving in the direction that reduces the cost function.

Question 3

What is a confusion matrix used to evaluate?

Accepted Answer

Classification model performance across all classes

Answer

A confusion matrix shows counts of true positives, false positives, true negatives, and false negatives for a classifier.

Question 4

In machine learning, what does 'hyperparameter tuning' refer to?

Accepted Answer

Selecting model parameters that are set before training

Answer

Hyperparameter tuning searches for the best configuration values (e.g., learning rate, depth) that are set before training begins.

Question 5

What does PCA (Principal Component Analysis) accomplish?

Accepted Answer

Reduces dimensionality by projecting data onto principal components

Answer

PCA finds orthogonal axes of maximum variance and projects data onto fewer dimensions while preserving variance.

Artificial Intelligence Practice Test