図書

Chapman & Hall/CRC data mining and knowledge discovery series

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Chapman & Hall/CRC data mining and knowledge discovery series

Material type
図書
Author
-
Publisher
Chapman & Hall/CRC
Publication date
c2007-
Material Format
Paper
Capacity, size, etc.
-
NDC
-
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Notes on use

Note (General):

Publisher varies: CRC Press

Related materials as well as pre- and post-revision versions

Data mining with R : learning with case studiesLeave the NDL website. Support vector machines : optimization based theory, algorithms, and extensionsLeave the NDL website. Temporal data miningLeave the NDL website. Computational intelligent data analysis for sustainable developmentLeave the NDL website. Constrained clustering : advances in algorithms, theory, and applicationsLeave the NDL website. Geographic data mining and knowledge discoveryLeave the NDL website. Data mining for design and marketingLeave the NDL website. Computational methods of feature selectionLeave the NDL website. Music data miningLeave the NDL website. Multimedia data mining : a systematic introduction to concepts and theoryLeave the NDL website. Mining software specifications : methodologies and applicationsLeave the NDL website. Contrast data mining : concepts, algorithms, and applicationsLeave the NDL website. Practical graph mining with RLeave the NDL website. Information discovery on electronic health recordsLeave the NDL website. Feature engineering for machine learning and data analyticsLeave the NDL website. Advances in machine learning and data mining for astronomyLeave the NDL website. Privacy-aware knowledge discovery : novel applications and new techniquesLeave the NDL website. Industrial applications of machine learningLeave the NDL website. Next generation of data miningLeave the NDL website. Introduction to privacy-preserving data publishing : concepts and techniquesLeave the NDL website. The top ten algorithms in data miningLeave the NDL website. Text mining : classification, clustering, and applicationsLeave the NDL website. Data mining with R : learning with case studiesLeave the NDL website. Data clustering : algorithms and applicationsLeave the NDL website. Relational data clustering : models, algorithms, and applicationsLeave the NDL website. Human capital systems, analytics, and data miningLeave the NDL website. Automated data analysis using ExcelLeave the NDL website. Biological data miningLeave the NDL website. Exploratory data analysis using RLeave the NDL website. Data science and analytics with PythonLeave the NDL website. Data clustering in C++ : an object-oriented approachLeave the NDL website. Social networks with rich edge semanticsLeave the NDL website. Accelerating discovery : mining unstructured information for hypothesis generationLeave the NDL website. Foundations of predictive analyticsLeave the NDL website. Computational business analyticsLeave the NDL website. Large-scale machine learning in the earth sciencesLeave the NDL website. Understanding complex datasets : data mining with matrix decompositionsLeave the NDL website. Spectral feature selection for data miningLeave the NDL website. Knowledge discovery from data streamsLeave the NDL website. Data mining : a tutorial-based primerLeave the NDL website. Temporal data miningLeave the NDL website. Handbook of educational data miningLeave the NDL website. RapidMiner : data mining use cases and business analytics applicationsLeave the NDL website. Data classification : algorithms and applicationsLeave the NDL website. Advanced data science and analytics with PythonLeave the NDL website. Advanced data science and analytics with PythonLeave the NDL website. Data science and machine learning for non-programmers : using SAS Enterprise minerLeave the NDL website. Automated data analysis using ExcelLeave the NDL website.

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Table of Contents

  • Data mining with R : learning with case studies

  • Support vector machines : optimization based theory, algorithms, and extensions

  • Temporal data mining

  • Computational intelligent data analysis for sustainable development

  • Constrained clustering : advances in algorithms, theory, and applications

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Paper

Material Type
図書
Publication, Distribution, etc.
Publication Date
c2007-
Publication Date (W3CDTF)
2007
Alternative Title
Data mining and knowledge discovery series
Chapman & Hall/CRC data mining and knowledge series
Place of Publication (Country Code)
us
Target Audience
一般
Note (General)
Publisher varies: CRC Press
Related Material
Data mining with R : learning with case studies
Support vector machines : optimization based theory, algorithms, and extensions
Temporal data mining
Computational intelligent data analysis for sustainable development
Constrained clustering : advances in algorithms, theory, and applications
Geographic data mining and knowledge discovery
Data mining for design and marketing
Computational methods of feature selection
Music data mining
Multimedia data mining : a systematic introduction to concepts and theory
Mining software specifications : methodologies and applications
Contrast data mining : concepts, algorithms, and applications
Practical graph mining with R
Information discovery on electronic health records
Feature engineering for machine learning and data analytics
Advances in machine learning and data mining for astronomy
Privacy-aware knowledge discovery : novel applications and new techniques
Industrial applications of machine learning
Next generation of data mining
Introduction to privacy-preserving data publishing : concepts and techniques
The top ten algorithms in data mining
Text mining : classification, clustering, and applications
Data mining with R : learning with case studies
Data clustering : algorithms and applications
Relational data clustering : models, algorithms, and applications
Human capital systems, analytics, and data mining
Automated data analysis using Excel
Biological data mining
Exploratory data analysis using R
Data science and analytics with Python
Data clustering in C++ : an object-oriented approach
Social networks with rich edge semantics
Accelerating discovery : mining unstructured information for hypothesis generation
Foundations of predictive analytics
Computational business analytics
Large-scale machine learning in the earth sciences
Understanding complex datasets : data mining with matrix decompositions
Spectral feature selection for data mining
Knowledge discovery from data streams
Data mining : a tutorial-based primer
Temporal data mining
Handbook of educational data mining
RapidMiner : data mining use cases and business analytics applications
Data classification : algorithms and applications
Advanced data science and analytics with Python
Advanced data science and analytics with Python
Data science and machine learning for non-programmers : using SAS Enterprise miner
Automated data analysis using Excel