MS-DS Master of Data science Master of Data science Supervised Learning Algorithms 1

Question 1

Which of the following algorithms builds an ensemble by training each new model to correct the errors made by the previous models sequentially?

Accepted Answer

AdaBoost

Answer

AdaBoost (Adaptive Boosting) sequentially trains weak learners, assigning higher weights to misclassified samples so that each subsequent learner focuses on the errors of its predecessor.

Question 2

In a decision tree, which criterion measures the impurity of a node by computing the probability that two randomly chosen samples belong to different classes?

Accepted Answer

Gini Impurity

Answer

Gini Impurity measures node impurity as 1 minus the sum of squared class probabilities, representing the likelihood that a randomly selected sample would be incorrectly classified.

Question 3

What is the primary purpose of the kernel trick in Support Vector Machines?

Accepted Answer

To implicitly map input features into a higher-dimensional space without computing the transformation explicitly

Answer

The kernel trick allows SVMs to find a linear separating hyperplane in a higher-dimensional feature space by computing inner products via a kernel function, avoiding the computational cost of explicit transformation.

Question 4

In logistic regression, which function maps the raw linear output to a probability between 0 and 1?

Accepted Answer

Sigmoid function

Answer

The sigmoid (logistic) function σ(z) = 1/(1+e^−z) squashes any real-valued linear combination of features into the (0,1) interval, making it suitable for binary probability estimation.

Question 5

Which evaluation metric is most appropriate when the cost of false negatives is much higher than the cost of false positives in a binary classification problem?

Accepted Answer

Recall (Sensitivity)

Answer

Recall (TP / (TP + FN)) directly measures how many actual positives are correctly identified, making it the priority metric when missing a positive case (false negative) is especially costly, such as in medical diagnosis.

MS-DS Master of Data science Practice Test

MS-DS Master of Data science Practice Test

MS-DS Master of Data science Master of Data science Supervised Learning Algorithms 1