10) Clustering analysis is used to separate objects into groups and, based on their characteristics, identify similar objects. This type of algorit...

10) Clustering analysis is used to separate objects into groups and, based on their characteristics, identify similar objects. This type of algorithm can be classified in several ways, such as hierarchical methods, density-based methods, or quadratic error-based methods. Analyze the following statements about clustering algorithms: I. The agglomerative hierarchical clustering technique makes each element a cluster, then groups similar clusters, calculates distances between clusters, and repeats this process until all elements are in the same cluster. II. The k-means algorithm is a density-based clustering algorithm that groups data points into k clusters based on their proximity to the centroid of each cluster. III. The DBSCAN algorithm is a quadratic error-based clustering algorithm that groups data points into clusters based on their density and distance from each other. Choose the alternative that correctly judges these statements:

I. The agglomerative hierarchical clustering technique makes each element a cluster, then groups similar clusters, calculates distances between clusters, and repeats this process until all elements are in the same cluster.
II. The k-means algorithm is a density-based clustering algorithm that groups data points into k clusters based on their proximity to the centroid of each cluster.
III. The DBSCAN algorithm is a quadratic error-based clustering algorithm that groups data points into clusters based on their density and distance from each other.
a. Only II and III are correct.
b. Only III is correct.
c. Only I and III are correct.
d. Only I is correct.
e. Only II is correct.