Pregled bibliografske jedinice broj: 867207
Particle Swarm Optimization Algorithm as a Tool for Profiling from Predictive Data Mining Models
Particle Swarm Optimization Algorithm as a Tool for Profiling from Predictive Data Mining Models // Nature-Inspired Computing: Concepts, Methodologies, Tools, and Applications (3 Volumes) / Information Resources Management Association (USA) (ur.)., 2017. str. 864-892
CROSBI ID: 867207 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Particle Swarm Optimization Algorithm as a Tool for Profiling from Predictive Data Mining Models
Autori
Klepac, Goran
Vrsta, podvrsta i kategorija rada
Poglavlja u knjigama, znanstveni
Knjiga
Nature-Inspired Computing: Concepts, Methodologies, Tools, and Applications (3 Volumes)
Urednik/ci
Information Resources Management Association (USA)
Izdavač
IGI Global
Godina
2017
Raspon stranica
864-892
ISBN
9781522507888
Ključne riječi
Data Mining
Sažetak
This chapter introduces the methodology of particle swarm optimization algorithm usage as a tool for finding customer profiles based on a previously developed predictive model that predicts events like selection of some products or services with some probabilities. Particle swarm optimization algorithm is used as a tool that finds optimal values of input variables within developed predictive models as referent values for maximization value of probability that customers select/buy a product or service. Recognized results are used as a base for finding similar profiles between customers. The presented methodology has practical value for decision support in business, where information about customer profiles are valuable information for campaign planning and customer portfolio management.
Izvorni jezik
Engleski
Znanstvena područja
Informacijske i komunikacijske znanosti
