Question 1

What is the primary objective of k-means clustering?

Options :

A : Classification

B : Association Rule Learning

C : Regression

D : Dimensionality Reduction

E : Clustering

F : Anomaly Detection

Answer: E

Question 2

Which of the following is an example of supervised learning?

Options :

A : K-means

B : Unsupervised Learning

C : Linear Regression

D : Linear Regression

Answer: D

Question 3

Which of these is a benefit of using convolutional neural networks (CNNs) for image processing?

Options :

A : They require smaller datasets

B : They are less computationally intensive

C : They automatically detect important features

D : They do not require labeled data

Answer: C

Question 4

In which phase of the machine learning process are hyperparameters tuned to optimize model performance?

Options :

A : Model Deployment

B : Model Evaluation

C : Model Training

D : Feature Engineering

E : Hyperparameter Tuning

F : Data Preprocessing

Answer: E

Question 5

Which of these metrics is used to evaluate a classifier's performance?

Options :

A : Accuracy

B : Mean Squared Error

Correct selection

C : Precision

D : Recall

E : F1 Score

F : Root Mean Squared Error

Answer: A,C,D,E