MTS488 Quiz 4

What is the primary goal of cluster analysis?

• To predict future data trends

• To classify data into distinct categories

• To group similar objects into clusters

• To visualize data in three dimensions

Which of the following is NOT an application of cluster analysis?

• Biology studies

• Marketing

• Insurance

• Web development

What is a key feature of a good clustering algorithm?

• It should produce random results

• It should only work with large datasets

• It should be able to handle noisy data

• It should require extensive user guidance

Which distance metric is defined as the maximum value of differences along any coordinate dimension?

• Euclidean distance

• Chebyshev distance

• Cosine distance

• Manhattan distance

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

• The number of dimensions

• The number of data points

• The number of clusters

• The number of iterations

Which clustering algorithm is sensitive to outliers?

• Agglomerative clustering

• K-means clustering

• DBSCAN

• Hierarchical clustering

What does DBSCAN stand for?

• Data-Based Statistical Clustering of Applications with Noise

• Density-Based Statistical Clustering of Applications with Noise

• Data-Based Spatial Clustering of Applications with Noise

• Density-Based Spatial Clustering of Applications with Noise

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

• It works well with overlapping clusters

• It is not sensitive to initial seed selection

• It requires a predefined number of clusters

• It can handle categorical data

What is the main characteristic of density-based clustering?

• It forms clusters based on distance from a centroid

• It identifies clusters based on density distribution

• It requires a fixed number of clusters

• It only works with numerical data

Which clustering method generates a hierarchy of clusters?

• Partitioning method

• Hierarchical method

• Density-based method

• Model-based method