Classification methods for internet applications

• 作者： Holena, Martin, author.
• 其他作者：
  • Pulc, Petr, author.
  • Kopp, Martin, author.
  • SpringerLink (Online service)
• 其他題名：
  • Studies in big data ;
• 出版： Cham : Springer International Publishing :Imprint: Springer
• 叢書名： Studies in big data,volume 69
• 主題： Information filtering systems. , Classification rule mining. , Computational Intelligence. , Data Mining and Knowledge Discovery. , Probability and Statistics in Computer Science. , Pattern Recognition.
• ISBN： 9783030369620 (electronic bk.) 、 9783030369613 (paper)
• FIND@SFXID: CGU
• 資料類型: 電子書
• 內容註: 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.
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• 摘要註: 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.
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