Final ML

What is K-means primarily used for?

• Dimensionality reduction

• Clustering

• Classification

• Regression

Which algorithm is used for density-based clustering?

• K-means

• DBSCAN

• t-SNE

• PCA

Which of the following is an unsupervised learning algorithm?

• Decision Trees

• DBSCAN

• t-SNE

• Factorization of non-negative matrices

hat does t-SNE stand for?

• T-distributed Stochastic Neighbor Embedding

• Tree-Structured Neighborhood Embedding

• Time Series Network Evaluation

• Title Statistics Nether Embed

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

• By the user input

• Automatically by the algorithm

• Randomly

• Typically

Which algorithm is sensitive to outliers?

• K-means

• DBSCAN

• Decision Trees

• Random Forest

Which of the following is a hierarchical clustering algorithm?

• K-means

• DBSCAN

• t-SNE

• Factorization of non-negative matrices

What is the main disadvantage of Decision Trees?

• They are prone to overfitting

• They cannot handle categorical data

• They are computationally expensive

• All the above

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

• K-means

• DBSCAN

• Decision Trees

• PCA

What type of machine learning algorithm is t-SNE?

• Supervised

• Unsupervised

• Reinforcement

• Supervisor