ml354535

What is K-means primarily used for?

• A) Dimensionality reduction

• B) Clustering

• C) Classification

Which algorithm is used for density-based clustering?

• A) K-means

• B) DBSCAN

• C) t-SNE

Which of the following is an unsupervised learning algorithm?

• A) Decision Trees

• B) DBSCAN

• C) t-SNE

What does t-SNE stand for?

• A) T-distributed Stochastic Neighbor Embedding

• B) Tree-Structured Neighborhood Embedding

• C) Time Series Network Evaluation

In K-means clustering, how is the number of clusters determined?

• A) By the user input

• B) Automatically by the algorithm

• C) Randomly

In K-means clustering, how is the number of clusters determined?

• A) By the user input

• B) Automatically by the algorithm

• C) Randomly

Which algorithm is sensitive to outliers?

• A) K-means

• B) DBSCAN

• C) Decision Trees

Which of the following is a hierarchical clustering algorithm?

• A) K-means

• B) DBSCAN

• C) t-SNE

What is the main disadvantage of Decision Trees?

• A) They are prone to overfitting

• B) They cannot handle categorical data

• C) They are computationally expensive

Which clustering algorithm does not require the user to specify the number of clusters?

• A) K-means

• B) DBSCAN

• C) Decision Trees