Cem Iyigun
METU, Department of Industrial Engineering
May 23, Wednesday 11:40-12:30
Institute of Applied Math, S209
Clustering is a process of partitioning (classification) of data points (observations, patterns) into disjoint groups (clusters) of similar objects. The search for clusters is a method of unsupervised learning, used in many areas, including statistics, machine learning, data mining, operations research, bioinformatics, facility location, and across multiple application areas including genetics, taxonomy, medicine, marketing, finance, and e-commerce.This talk presents an overview of clustering methods and reviews the different clustering algorithms and methods and gives the mathematical approaches to clustering problems.