Question 1

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 2

What is the purpose of dimensionality reduction in machine learning?

Options :

A : Data Augmentation

B : Model Evaluation

C : Model Regularization

D : Feature Extraction

E : Model Interpretation

F : Noise Reduction

Answer: D

Question 3

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 4

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

Question 5

What is the purpose of the "learning rate" in gradient descent?

Options :

A : To control the speed of model training

B : To adjust the weight of input features

C : To determine the number of layers in a neural network

D : To set the threshold for classification

Answer: A