↓ Skip to main content

SVM-OD: SVM method to detect outliers

Overview of attention for book
Cover of 'SVM-OD: SVM method to detect outliers'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Commonsense Causal Modeling in the Data Mining Context
  3. Altmetric Badge
    Chapter 2 Definability of Association Rules in Predicate Calculus
  4. Altmetric Badge
    Chapter 3 A Measurement-Theoretic Foundation of Rule Interestingness Evaluation
  5. Altmetric Badge
    Chapter 4 Statistical Independence as Linear Dependence in a Contingency Table
  6. Altmetric Badge
    Chapter 5 Foundations of Classification
  7. Altmetric Badge
    Chapter 6 Data Mining as Generalization: A Formal Model
  8. Altmetric Badge
    Chapter 7 SVM-OD: SVM Method to Detect Outliers1
  9. Altmetric Badge
    Chapter 8 Extracting Rules from Incomplete Decision Systems: System ERID
  10. Altmetric Badge
    Chapter 9 Mining for Patterns Based on Contingency Tables by KL-Miner – First Experience
  11. Altmetric Badge
    Chapter 10 Knowledge Discovery in Fuzzy Databases Using Attribute-Oriented Induction
  12. Altmetric Badge
    Chapter 11 Rough Set Strategies to Data with Missing Attribute Values
  13. Altmetric Badge
    Chapter 12 Privacy-Preserving Collaborative Data Mining
  14. Altmetric Badge
    Chapter 13 Impact of Purity Measures on Knowledge Extraction in Decision Trees
  15. Altmetric Badge
    Chapter 14 Multidimensional On-line Mining
  16. Altmetric Badge
    Chapter 15 Quotient Space Based Cluster Analysis1
  17. Altmetric Badge
    Chapter 16 Research Issues in Web Structural Delta Mining
  18. Altmetric Badge
    Chapter 17 Workflow Reduction for Reachable-path Rediscovery in Workflow Mining
  19. Altmetric Badge
    Chapter 18 Principal Component-based Anomaly Detection Scheme
  20. Altmetric Badge
    Chapter 19 Making Better Sense of the Demographic Data Value in the Data Mining Procedure
  21. Altmetric Badge
    Chapter 20 An Effective Approach for Mining Time-Series Gene Expression Profile
Overall attention for this book and its chapters
Altmetric Badge

Mentioned by

twitter
26 X users

Citations

dimensions_citation
1 Dimensions

Readers on

mendeley
21 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
SVM-OD: SVM method to detect outliers
Published by
Springer-Verlag Berlin, January 2006
DOI 10.1007/11539827
ISBNs
978-3-54-028315-7, 978-3-54-031229-1
Authors

Wang, J, Zhang, C, Wu, X, Qi, H

Editors

Young Lin, Tsau, Ohsuga, Setsuo, Liau, Churn-Jung, Hu, Xiaohua

X Demographics

X Demographics

The data shown below were collected from the profiles of 26 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 21 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 24%
Researcher 3 14%
Student > Master 3 14%
Student > Bachelor 2 10%
Student > Doctoral Student 2 10%
Other 4 19%
Unknown 2 10%
Readers by discipline Count As %
Computer Science 8 38%
Engineering 4 19%
Psychology 2 10%
Mathematics 2 10%
Physics and Astronomy 2 10%
Other 1 5%
Unknown 2 10%