Quiz on Hierarchical Clustering

What is the primary goal of clustering?

• To predict future data points

• To group similar data points

• To classify data into predefined categories

• To visualize data in 3D

Which type of clustering assigns each data point to a single cluster?

• Hierarchical Clustering

• Hard Clustering

• Soft Clustering

• K-Means Clustering

What does a dendrogram represent?

• The average distance of clusters

• The probability of data points belonging to clusters

• The hierarchical relationship between clusters

• The distance between data points

Agglomerative clustering follows which approach?

• Random

• Linear

• Top-down

• Bottom-up

In soft clustering, what is evaluated for each data point?

• Average distance to all clusters

• Exact cluster membership

• Probability of belonging to multiple clusters

• Distance to the nearest cluster

What is the main characteristic of divisive clustering?

• It merges clusters based on proximity

• It splits a large cluster into smaller ones

• It uses a fixed number of clusters

• It requires labeled data

Which clustering method is known for identifying small clusters effectively?

• K-Means Clustering

• Density-Based Clustering

• Agglomerative Clustering

• Divisive Clustering

What is the agglomerative coefficient used for?

• To calculate distances between points

• To determine the number of clusters

• To measure the quality of clustering

• To visualize clusters

Which of the following is NOT a step in agglomerative clustering?

• Compute the proximity matrix

• Merge clusters based on similarity

• Split clusters into smaller groups

• Repeat until one cluster remains

What does the divisive coefficient assess?

• The quality of agglomerative clustering

• The distance between clusters

• The quality of divisive clustering

• The efficiency of K-Means clustering