Data mining: concepts, models, methods, and algorithms
Presents the latest techniques for analyzing and extracting information from large amounts of data in high-dimensional data spaces The revised and updated third edition of Data Mining contains in one volume an introduction to a systematic approach to the analysis of large data sets that integrates r...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Hoboken
Wiley
[2020]
|
| Ausgabe: | Third edition |
| Schriftenreihe: | IEEE Press
|
| Schlagworte: | |
| Online-Zugang: | FHN01 Volltext |
| Zusammenfassung: | Presents the latest techniques for analyzing and extracting information from large amounts of data in high-dimensional data spaces The revised and updated third edition of Data Mining contains in one volume an introduction to a systematic approach to the analysis of large data sets that integrates results from disciplines such as statistics, artificial intelligence, data bases, pattern recognition, and computer visualization. Advances in deep learning technology have opened an entire new spectrum of applications. The author'a noted expert on the topic'explains the basic concepts, models, and methodologies that have been developed in recent years. This new edition introduces and expands on many topics, as well as providing revised sections on software tools and data mining applications. Additional changes include an updated list of references for further study, and an extended list of problems and questions that relate to each chapter.This third edition presents new and expanded information that: -''' Explores big data and cloud computing -''' Examines deep learning -''' Includes information on convolutional neural networks (CNN) -''' Offers reinforcement learning -''' Contains semi-supervised learning and S3VM -''' Reviews model evaluation for unbalanced data Written for graduate students in computer science, computer engineers, and computer information systems professionals, the updated third edition of Data Mining continues to provide an essential guide to the basic principles of the technology and the most recent developments in the field |
| Beschreibung: | 1 Online-Ressource (xix, 639 Seiten) Diagramme |
| ISBN: | 9781119515982 |
Internformat
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| id | DE-604.BV046260043 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T08:39:50Z |
| institution | BVB |
| isbn | 9781119515982 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-031638066 |
| oclc_num | 1129397105 |
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| physical | 1 Online-Ressource (xix, 639 Seiten) Diagramme |
| psigel | ZDB-30-PQE |
| publishDate | 2020 |
| publishDateSearch | 2020 |
| publishDateSort | 2020 |
| publisher | Wiley |
| record_format | marc |
| series2 | IEEE Press |
| spelling | Kantardzic, Mehmed 1947- Verfasser (DE-588)1244240834 aut Data mining concepts, models, methods, and algorithms Mehmed Kantardzic Third edition Hoboken Wiley [2020] 1 Online-Ressource (xix, 639 Seiten) Diagramme txt rdacontent c rdamedia cr rdacarrier IEEE Press Presents the latest techniques for analyzing and extracting information from large amounts of data in high-dimensional data spaces The revised and updated third edition of Data Mining contains in one volume an introduction to a systematic approach to the analysis of large data sets that integrates results from disciplines such as statistics, artificial intelligence, data bases, pattern recognition, and computer visualization. Advances in deep learning technology have opened an entire new spectrum of applications. The author'a noted expert on the topic'explains the basic concepts, models, and methodologies that have been developed in recent years. This new edition introduces and expands on many topics, as well as providing revised sections on software tools and data mining applications. Additional changes include an updated list of references for further study, and an extended list of problems and questions that relate to each chapter.This third edition presents new and expanded information that: -''' Explores big data and cloud computing -''' Examines deep learning -''' Includes information on convolutional neural networks (CNN) -''' Offers reinforcement learning -''' Contains semi-supervised learning and S3VM -''' Reviews model evaluation for unbalanced data Written for graduate students in computer science, computer engineers, and computer information systems professionals, the updated third edition of Data Mining continues to provide an essential guide to the basic principles of the technology and the most recent developments in the field Data mining COMPUTERS / Databases / Data Mining Electronic books Erscheint auch als Druck-Ausgabe, Hardcover 978-1-119-51604-0 (DE-604)BV046643054 https://ebookcentral.proquest.com/lib/thnuernberg/detail.action?docID=5966761 Aggregator URL des Erstveröffentlichers Volltext |
| spellingShingle | Kantardzic, Mehmed 1947- Data mining concepts, models, methods, and algorithms |
| title | Data mining concepts, models, methods, and algorithms |
| title_auth | Data mining concepts, models, methods, and algorithms |
| title_exact_search | Data mining concepts, models, methods, and algorithms |
| title_full | Data mining concepts, models, methods, and algorithms Mehmed Kantardzic |
| title_fullStr | Data mining concepts, models, methods, and algorithms Mehmed Kantardzic |
| title_full_unstemmed | Data mining concepts, models, methods, and algorithms Mehmed Kantardzic |
| title_short | Data mining |
| title_sort | data mining concepts models methods and algorithms |
| title_sub | concepts, models, methods, and algorithms |
| url | https://ebookcentral.proquest.com/lib/thnuernberg/detail.action?docID=5966761 |
| work_keys_str_mv | AT kantardzicmehmed dataminingconceptsmodelsmethodsandalgorithms |