ML SLIV

What is K-means primarily used for?

• Dimensionality reduction

• Clustering

• Classification

• Regression

Which algorithm is used for density-based clustering?

• K-means

• B) DBSCAN

• C) t-SNE

• D) PCA

Which of the following is an unsupervised learning algorithm?

• A) Decision Trees

• B) DBSCAN

• C) t-SNE

• D) Factorization of non-negative matrices

What does t-SNE stand for?

• A) T-distributed Stochastic Neighbor Embedding

• B) Tree-Structured Neighborhood Embedding

• C) Time Series Network Evaluation

• D) Title Statistics Nether Embed

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

• A) By the user input

• B) Automatically by the algorithm

• C) Randomly

• D) Typically

Which algorithm is sensitive to outliers?

• A) K-means

• B) DBSCAN

• C) Decision Trees

• D) Random Forest

Which of the following is a hierarchical clustering algorithm?

• A)K-means

• B)DBSCAN

• C)t-SNE

• D)Factorization of non-negative matrices

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

• D)All the above

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

• A)K-means

• B)DBSCAN

• C)Decision Trees

• D)PCA

What type of machine learning algorithm is t-SNE?

• A)Supervised

• B)Unsupervised

• C) Reinforcement

• D)Supervisor