The concepts of centrality and vary are extraordinarily important in search algorithms, and play central roles in functions of artificial intelligence (AI), machine finding out (ML), social networks, and pattern recognition. This work examines the significance of centrality and vary in illustration, regression, ranking, clustering, optimization, and classification. The textual content material is designed to be accessible to a broad readership. Requiring solely a elementary background in undergraduate-level arithmetic, the work is suitable for senior undergraduate and graduate faculty college students, in addition to researchers working in machine finding out, data mining, social networks, and pattern recognition. |