DSE Knowledge 4

Question 1

What distinguishes supervised learning from unsupervised learning?

Accepted Answer

Supervised learning trains on labeled input-output pairs; unsupervised learning finds structure in unlabeled data

Answer

Supervised learning maps inputs to known outputs using labeled examples, while unsupervised learning discovers hidden patterns in data without labels.

Question 2

Which metric is most appropriate for evaluating a classifier on a heavily imbalanced dataset?

Accepted Answer

F1-Score or AUC-ROC

Answer

F1-Score and AUC-ROC account for class imbalance, whereas accuracy can be misleadingly high when the majority class dominates.

Question 3

In gradient descent, what does the learning rate control?

Accepted Answer

The step size taken in the direction of the negative gradient at each update

Answer

The learning rate scales the gradient update step; too large causes divergence, too small causes slow convergence.

Question 4

What type of relationship does Pearson correlation measure?

Accepted Answer

Linear relationship between two continuous variables

Answer

Pearson correlation measures the strength and direction of the linear association between two continuous variables, ranging from -1 to +1.

Question 5

Which of the following is a key assumption of linear regression?

Accepted Answer

There is a linear relationship between predictors and the response variable

Answer

Linear regression assumes the expected value of the outcome is a linear combination of the predictor variables.

DSE - Data Science Practice Test

DSE - Data Science Practice Test

DSE Knowledge 4