MS-DS Master of Data science MS-DS Master of Data science Supervised Learning Algorithms Questions and Answers 3

Question 1

What does the C parameter control in a Support Vector Machine classifier?

Accepted Answer

The trade-off between maximizing the margin and minimizing classification error

Answer

The C parameter controls how much the model penalizes misclassified points versus maintaining a wider margin.

Question 2

Which metric is most appropriate for evaluating a supervised learning model on a highly imbalanced binary classification dataset?

Accepted Answer

Area Under the Precision-Recall Curve

Answer

The precision-recall AUC is more informative than accuracy when the class distribution is heavily skewed.

Question 3

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

Accepted Answer

The probability of incorrectly classifying a randomly chosen element

Answer

Gini impurity measures the likelihood that a randomly selected sample would be misclassified if labeled according to the class distribution at that node.

Question 4

What is the main advantage of AdaBoost over a single decision tree?

Accepted Answer

It sequentially focuses on misclassified samples to improve overall accuracy

Answer

AdaBoost assigns higher weights to misclassified samples in each iteration, forcing subsequent weak learners to focus on harder examples.

Question 5

Which supervised learning algorithm models the probability of a binary outcome using the sigmoid function?

Accepted Answer

Logistic Regression

Answer

Logistic regression applies the sigmoid function to a linear combination of features to output a probability between 0 and 1.

MS-DS Master of Data science Practice Test

MS-DS Master of Data science Practice Test

MS-DS Master of Data science MS-DS Master of Data science Supervised Learning Algorithms Questions and Answers 3