Coverart for item
The Resource Principles of data mining, Max Bramer

Principles of data mining, Max Bramer

Label
Principles of data mining
Title
Principles of data mining
Statement of responsibility
Max Bramer
Creator
Subject
Language
eng
Summary
Data Mining, the automatic extraction of implicit and potentially useful information from data, is increasingly used in commercial, scientific and other application areas. Principles of Data Mining explains and explores the principal techniques of Data Mining: for classification, association rule mining and clustering. Each topic is clearly explained and illustrated by detailed worked examples, with a focus on algorithms rather than mathematical formalism. It is written for readers without a strong background in mathematics or statistics, and any formulae used are explained in detail. This second edition has been expanded to include additional chapters on using frequent pattern trees for Association Rule Mining, comparing classifiers, ensemble classification and dealing with very large volumes of data. Principles of Data Mining aims to help general readers develop the necessary understanding of what is inside the 'black box' so they can use commercial data mining packages discriminatingly, as well as enabling advanced readers or academic researchers to understand or contribute to future technical advances in the field. Suitable as a textbook to support courses at undergraduate or postgraduate levels in a wide range of subjects including Computer Science, Business Studies, Marketing, Artificial Intelligence, Bioinformatics and Forensic Science
Member of
Cataloging source
GW5XE
http://library.link/vocab/creatorDate
1948-
http://library.link/vocab/creatorName
Bramer, M. A.
Dewey number
006.312
Illustrations
illustrations
Index
index present
LC call number
QA76.9.D343
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
NLM call number
QA 76.9.D343
Series statement
Undergraduate topics in computer science
http://library.link/vocab/subjectName
  • Data mining
  • Data Mining
  • Data mining
Label
Principles of data mining, Max Bramer
Instantiates
Publication
Antecedent source
unknown
Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
  • Avoiding Overfitting of Decision Trees
  • More About Entropy
  • Inducing Modular Rules for Classification
  • Measuring the Performance of a Classifier
  • Dealing with Large Volumes of Data
  • Ensemble Classification
  • Comparing Classifiers
  • Association Rule Mining I
  • Association Rule Mining II
  • Association Rule Mining III: Frequent Pattern Trees
  • Introduction to Data Mining
  • Clustering
  • Text Mining
  • Data for Data Mining
  • Introduction to Classification: Naïve Bayes and Nearest Neighbour
  • Using Decision Trees for Classification
  • Decision Tree Induction: Using Entropy for Attribute Selection
  • Decision Tree Induction: Using Frequency Tables for Attribute Selection
  • Estimating the Predictive Accuracy of a Classifier
  • Continuous Attributes
Control code
828676626
Dimensions
unknown
Edition
2nd ed.
Extent
1 online resource.
File format
unknown
Form of item
online
Isbn
9781447148845
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Other control number
10.1007/978-1-4471-4884-5
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
System control number
(OCoLC)828676626
Label
Principles of data mining, Max Bramer
Publication
Antecedent source
unknown
Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
  • Avoiding Overfitting of Decision Trees
  • More About Entropy
  • Inducing Modular Rules for Classification
  • Measuring the Performance of a Classifier
  • Dealing with Large Volumes of Data
  • Ensemble Classification
  • Comparing Classifiers
  • Association Rule Mining I
  • Association Rule Mining II
  • Association Rule Mining III: Frequent Pattern Trees
  • Introduction to Data Mining
  • Clustering
  • Text Mining
  • Data for Data Mining
  • Introduction to Classification: Naïve Bayes and Nearest Neighbour
  • Using Decision Trees for Classification
  • Decision Tree Induction: Using Entropy for Attribute Selection
  • Decision Tree Induction: Using Frequency Tables for Attribute Selection
  • Estimating the Predictive Accuracy of a Classifier
  • Continuous Attributes
Control code
828676626
Dimensions
unknown
Edition
2nd ed.
Extent
1 online resource.
File format
unknown
Form of item
online
Isbn
9781447148845
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Other control number
10.1007/978-1-4471-4884-5
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
System control number
(OCoLC)828676626

Library Locations

    • Ellis LibraryBorrow it
      1020 Lowry Street, Columbia, MO, 65201, US
      38.944491 -92.326012
    • Engineering Library & Technology CommonsBorrow it
      W2001 Lafferre Hall, Columbia, MO, 65211, US
      38.946102 -92.330125
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