Data Science Data Science MCQ 2

Question 1

Which technique is most appropriate for reducing the dimensionality of a dataset while preserving as much variance as possible?

Accepted Answer

Principal Component Analysis

Answer

PCA projects data onto orthogonal components ordered by the variance they capture.

Question 2

In a confusion matrix, what does precision measure?

Accepted Answer

True positives divided by all predicted positives

Answer

Precision is TP / (TP + FP), the fraction of positive predictions that are correct.

Question 3

Which method helps prevent overfitting by penalizing large model coefficients?

Accepted Answer

L2 (Ridge) regularization

Answer

Ridge regularization adds a penalty proportional to the squared magnitude of coefficients.

Question 4

What is the primary purpose of cross-validation?

Accepted Answer

To estimate model performance on unseen data more reliably

Answer

Cross-validation rotates train/test splits to give a more robust performance estimate.

Question 5

Which distance metric is most commonly used by default in K-means clustering?

Accepted Answer

Euclidean distance

Answer

K-means minimizes within-cluster sum of squared Euclidean distances.

Data Science Practice Test