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Record Nr. |
UNINA9910741141003321 |
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Autore |
Holeňa Martin |
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Titolo |
Classification Methods for Internet Applications / / by Martin Holeňa, Petr Pulc, Martin Kopp |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
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ISBN |
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Edizione |
[1st ed. 2020.] |
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Descrizione fisica |
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1 online resource (290 pages) |
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Collana |
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Studies in Big Data, , 2197-6503 ; ; 69 |
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Disciplina |
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Soggetti |
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Computational intelligence |
Data mining |
Mathematical statistics |
Pattern perception |
Computational Intelligence |
Data Mining and Knowledge Discovery |
Probability and Statistics in Computer Science |
Pattern Recognition |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references. |
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Nota di contenuto |
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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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Sommario/riassunto |
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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 |
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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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