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 number of support vectors

Answer

The kernel function degree

Answer

The number of iterations for convergence

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

Accuracy

Answer

Mean Squared Error

Answer

R-squared

Question 3

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

Accepted Answer

The probability of incorrectly classifying a randomly chosen element

Answer

The information gain at each split

Answer

The depth of the tree

Answer

The variance of the target variable

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

It requires less training data

Answer

It is less computationally expensive

Answer

It eliminates the need for hyperparameter tuning

Question 5

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

Accepted Answer

Logistic Regression

Answer

Linear Regression

Answer

Decision Tree

Answer

K-Nearest Neighbors

Question 6

What is the bias-variance trade-off in the context of supervised learning?

Accepted Answer

The balance between underfitting the training data and overfitting to noise

Answer

The trade-off between training speed and prediction accuracy

Answer

The balance between the number of features and the number of samples

Answer

The trade-off between model interpretability and computational cost