K-means2

Which of the following task can be achieved by PCA?

• Clustering

• Dimension Reduction

• Regression

• Dimension Expansion

Which of the following is/are hierarchical clustering?

• K-Means

• Fuzzy C-Means

• Agglomerative clustering

• Divisive clustering

What is the goal of agglomerative clustering?

• To split observations into smaller clusters based on their similarity

• To merge clusters into larger groups based on their similarity

• To randomly group observations into clusters

• To create clusters with a mix of both similar and dissimilar observations

What is K in K-means clustering?

• The number of features in the dataset

• The number of iterations required for the algorithm to converge

• The number of observations in the dataset

• The number of clusters in the dataset

How is the optimal value of K in K-means determined?

• it is determined by the analyst using some external methods

• it is determined automatically by the algorithm

• None of the above

What is the Ward’s distance?

• The nearest distance between a pair of observations not in the same cluster

• The distance between the center/centroid or mean values of the clusters

• A.The squared difference between individual observations and the cluster mean

• The farthest distance between a pair of observations not in the same cluster