18C5T13 Study Guide - Final Guide: Dbscan, Hierarchical Clustering, Cluster Analysis

• School: Jawaharlal Nehru Technological University - JNTU Kakinada
• Department: Engineering
• Course: 18C5T13

Document Summary

Different types of clustering, different types of clusters: agglomerative hierarchical clustering: basic agglomerative hierarchical clustering algorithm, dbscan: traditional density center-based approach, dbscan algorithm, strengths and weaknesses, overview : Before discussing specific clustering techniques, we provide some necessary background. First, we further define cluster analysis, illustrating why it is difficult and explaining its relationship to other techniques that group data. Cluster analysis groups data objects based only on information found in the data that describes the objects and their relationships. The goal is that the objects within a group be similar (or related) to one another and different from (or unrelated to) the objects in other groups. The greater the similarity (or homogeneity) within a group and the greater the difference between groups, the better or more distinct the clustering. In many applications, the notion of a cluster is not well defined.