Quiz on Cluster Analysis

What is the primary goal of cluster analysis?

• To predict future data trends

• To classify data into predefined categories

• To group similar data objects into clusters

• To visualize data in a two-dimensional space

Which of the following is a characteristic of a good clustering method?

• High computational cost

• High inter-class similarity

• Low intra-class similarity

• High intra-class similarity

In the k-means clustering algorithm, what does 'k' represent?

• The number of iterations

• The number of clusters

• The number of data points

• The number of features

What type of clustering does the k-medoids algorithm use?

• Randomly selected points as centers

• Hierarchical structure

• Actual data points as cluster centers

• Centroids as cluster centers

Which clustering method is known for handling noise and outliers effectively?

• K-medoids

• DBSCAN

• K-means

• Hierarchical clustering

What is a dendrogram?

• A statistical measure of cluster quality

• A method for calculating distances

• A visual representation of hierarchical clustering

• A type of clustering algorithm

Which of the following is NOT a type of clustering approach?

• Partitioning approach

• Regression approach

• Hierarchical approach

• Density-based approach

What does the term 'core point' refer to in DBSCAN?

• A point with no neighbors

• A point that is always at the center of a cluster

• A point with a minimum number of neighbors within a specified distance

• A point that is an outlier

Which of the following is a limitation of the k-means algorithm?

• It can handle categorical data

• It requires the number of clusters to be specified in advance

• It can discover clusters of any shape

• It is not sensitive to outliers

What is the main purpose of outlier analysis in data mining?

• To improve data entry accuracy

• To find data points that significantly differ from the rest

• To identify and remove noise from the data

• To enhance the clustering process