Beschreibung
InhaltsangabeData Mining and Knowledge Discovery Process.- The Knowledge Discovery Process.- Data Understanding.- Data.- Concepts of Learning, Classification, and Regression.- Knowledge Representation.- Data Preprocessing.- Databases, Data Warehouses, and OLAP.- Feature Extraction and Selection Methods.- Discretization Methods.- Data Mining: Methods for Constructing Data Models.- Unsupervised Learning: Clustering.- Unsupervised Learning: Association Rules.- Supervised Learning: Statistical Methods.- Supervised Learning: Decision Trees, Rule Algorithms, and Their Hybrids.- Supervised Learning: Neural Networks.- Text Mining.- Data Models Assessment.- Assessment of Data Models.- Data Security and Privacy Issues.- Data Security, Privacy and Data Mining.
Inhalt
Part I. Data Mining and Knowledge Discovery: Introduction.- Knowledge Discovery Process.- Part II. Data Understanding: Data.- Concepts of Learning, Classification and Regression.- Knowledge Representation.- Part III. Data Preprocessing: Databases, Data Warehouses and OLAP.- Feature Extraction and Selection Methods.- Discretization Methods.- Part IV. Data Mining: Methods forConstructing Data Models: Unsupervised Learning: Clustering.- Unsupervised Learning: Association Rules.- Supervised Learning: Statistical Methods.- Supervised Learning: Decision Trees, Rule Algorithms and Their Hybrids.- Supervised Learning:Neural Networks.- Text Mining.- Part V. Data Models Assessment: Assessment ofData Models.- Part VI Data Security and Privacy Issues: Security, Privacy and Data Mining.- Appendices: Overview of key mathematical concepts.
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Springer Verlag GmbH
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