Data Science Supervised Learning Models 2

Question 1

In a logistic regression model, what does the sigmoid function output represent?

Accepted Answer

A probability between 0 and 1

Answer

The sigmoid squashes the linear combination into a value between 0 and 1 interpreted as a probability.

Question 2

Which loss function is most appropriate for a binary classification task?

Accepted Answer

Binary cross-entropy

Answer

Binary cross-entropy penalizes confident wrong predictions and suits probabilistic binary outputs.

Question 3

What is the primary purpose of regularization (L1/L2) in supervised models?

Accepted Answer

Reduce overfitting by penalizing large weights

Answer

Regularization adds a penalty on coefficient magnitude to discourage overly complex models that overfit.

Question 4

Which model uses a margin-maximizing hyperplane to separate classes?

Accepted Answer

Support Vector Machine

Answer

SVMs find the hyperplane that maximizes the margin between the nearest points of each class.

Question 5

In a decision tree, what does the Gini impurity measure?

Accepted Answer

Probability of misclassifying a randomly chosen sample

Answer

Gini impurity quantifies how often a randomly labeled sample would be misclassified at a node.

Data Science Practice Test