Introduction to Connectivity-Based Clustering Answers 1. What is a significant advantage of connectivity-based clustering in terms of data quality? A. Demands low computational resources B. Relies on exact parameter selection for accuracy C. Less sensitive to noise compared to distance-based methods D. Highly sensitive to outliers Answer: Less sensitive to noise compared to distance-based methods (C) Connectivity-based clustering is designed to be less sensitive to noise and outliers, providing better quality under certain conditions. 2. Which of the following is a disadvantage associated with connectivity-based clustering? A. Involves low computational complexity B. Provides a hierarchical view of data C. Sensitivity to poorly constructed similarity graphs D. Offers high interpretability of results Answer: Sensitivity to poorly constructed similarity graphs (C) Poorly constructed similarity graphs can significantly affect the quality of clustering results, leading to spurious clusters. 3. In which application is connectivity-based clustering NOT typically used? A. Image segmentation B. Social network analysis C. Sorting numerical data arrays D. Bioinformatics Answer: Sorting numerical data arrays (C) Connectivity-based clustering is often used in areas like social network analysis, but not for sorting numerical data arrays. 4. What factor significantly influences the results of connectivitybased clustering? A. Use of distance metrics exclusively B. Assumptions about data distribution C. Type of visual representation D. Selection of similarity measure and connectivity threshold Answer: Selection of similarity measure and connectivity threshold (D) The parameters like the similarity measure and connectivity threshold are crucial in determining the effectiveness of connectivity-based clustering. 5. What should be considered when choosing a method for connectivity-based clustering? A. The historical performance of alternative methods B. The computational resources available for execution C. Completely independent of data characteristics D. Only the desired output structure Answer: The computational resources available for execution (B) It's important to take into account the computational resources available, as they directly impact the feasibility of using certain methods for clustering.