01328nam0 22003373i 450 USM159376420231121125916.0849627421720160323d2003 ||||0itac50 baspaesz01i xxxe z01nTeocrito, Arato, "Argonáuticas órficas"J. G. Montes Cala ... [et al.]CádizUniversidad de Cádiz, Servicio de Publ.Ediciones clasicas2003321 p.24 cm.Studia hellenistica gaditana1001USM16013682001 Studia hellenistica gaditana1Orfeo nella letteraturaFIRRMLC211900IArato : di SoliFIRRMLC385488ETeocritoFIRRMLC012657EPoesia grecaStoria e criticaFIRRMLC416181IMontes Cala, Jose GuillermoURBV064000ITIT-0120160323IT-FR0017 Biblioteca umanistica Giorgio ApreaFR0017 USM1593764Biblioteca umanistica Giorgio Aprea 52CIS 9/1884 52VM 0000680385 VM barcode:00044451. - Inventario:30296 FLSVMA 2007040320121204 52Teocrito, Arato, "Argonáuticas órficas"3642759UNICAS03690nam 22006495 450 991074114100332120200630162720.03-030-36962-510.1007/978-3-030-36962-0(CKB)4100000010122009(MiAaPQ)EBC6032967(DE-He213)978-3-030-36962-0(PPN)243767692(EXLCZ)99410000001012200920200129d2020 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierClassification Methods for Internet Applications /by Martin Holeňa, Petr Pulc, Martin Kopp1st ed. 2020.Cham :Springer International Publishing :Imprint: Springer,2020.1 online resource (290 pages)Studies in Big Data,2197-6503 ;693-030-36961-7 Includes bibliographical references.Important Internet Applications of Classification -- Basic Concepts Concerning Classification -- Some Frequently Used Classification Methods -- Aiming at Predictive Accuracy -- Aiming at Comprehensibility -- A Team Is Superior to an Individual.This book explores internet applications in which a crucial role is played by classification, such as spam filtering, recommender systems, malware detection, intrusion detection and sentiment analysis. It explains how such classification problems can be solved using various statistical and machine learning methods, including K nearest neighbours, Bayesian classifiers, the logit method, discriminant analysis, several kinds of artificial neural networks, support vector machines, classification trees and other kinds of rule-based methods, as well as random forests and other kinds of classifier ensembles. The book covers a wide range of available classification methods and their variants, not only those that have already been used in the considered kinds of applications, but also those that have the potential to be used in them in the future. The book is a valuable resource for post-graduate students and professionals alike.Studies in Big Data,2197-6503 ;69Computational intelligenceData miningMathematical statisticsPattern perceptionComputational Intelligencehttps://scigraph.springernature.com/ontologies/product-market-codes/T11014Data Mining and Knowledge Discoveryhttps://scigraph.springernature.com/ontologies/product-market-codes/I18030Probability and Statistics in Computer Sciencehttps://scigraph.springernature.com/ontologies/product-market-codes/I17036Pattern Recognitionhttps://scigraph.springernature.com/ontologies/product-market-codes/I2203XComputational intelligence.Data mining.Mathematical statistics.Pattern perception.Computational Intelligence.Data Mining and Knowledge Discovery.Probability and Statistics in Computer Science.Pattern Recognition.025.42Holeňa Martinauthttp://id.loc.gov/vocabulary/relators/aut1199351Pulc Petrauthttp://id.loc.gov/vocabulary/relators/autKopp Martinauthttp://id.loc.gov/vocabulary/relators/autMiAaPQMiAaPQMiAaPQBOOK9910741141003321Classification Methods for Internet Applications3553611UNINA