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 distributions

Which type of clustering assigns each data point completely to one cluster?

• Hard Clustering

• Hierarchical Clustering

• K-Means Clustering

• Soft Clustering

What does a dendrogram represent?

• The distance between data points

• The hierarchical relationship between clusters

• The probability of data point assignments

• The performance of clustering algorithms

Agglomerative clustering follows which approach?

• Random

• Top-down

• Iterative

• Bottom-up

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

• Distance to the nearest cluster

• Probability of belonging to multiple clusters

• Exact cluster membership

• Average distance to all points

What is the main characteristic of divisive clustering?

• It requires labeled data

• It merges clusters based on proximity

• It uses a fixed number of clusters

• It splits a large cluster into smaller ones

Which clustering method is known for identifying small clusters effectively?

• Density-Based Clustering

• K-Means Clustering

• Agglomerative Clustering

• Divisive Clustering

What is the agglomerative coefficient used for?

• To measure the quality of clustering

• To determine the number of clusters

• To visualize cluster relationships

• To calculate distances between points

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

• Split clusters into smaller groups

• Merge clusters based on similarity

• Repeat until one cluster remains

• Compute the proximity matrix

What is the main advantage of divisive clustering over agglomerative clustering?

• It requires fewer computations

• It can handle larger datasets

• It is more efficient

• It is easier to implement