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

A raw class label

Answer

The residual error

Answer

The feature variance

Question 2

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

Accepted Answer

Binary cross-entropy

Answer

Mean squared error

Answer

Mean absolute error

Answer

Huber loss

Question 3

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

Accepted Answer

Reduce overfitting by penalizing large weights

Answer

Increase training accuracy

Answer

Speed up gradient computation

Answer

Balance class labels

Question 4

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

Accepted Answer

Support Vector Machine

Answer

K-Means

Answer

Naive Bayes

Answer

Linear regression

Question 5

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

Accepted Answer

Probability of misclassifying a randomly chosen sample

Answer

Depth of the tree

Answer

Number of leaf nodes

Answer

Feature correlation

Question 6

What distinguishes a supervised model from an unsupervised one?

Accepted Answer

It trains on labeled target values

Answer

It requires no data

Answer

It only clusters data

Answer

It cannot make predictions

Question 7

Which metric is best for evaluating a classifier on an imbalanced dataset?

Accepted Answer

F1 score

Answer

Raw accuracy

Answer

Total training time

Answer

Number of features