↓ Skip to main content

Challenges in Computational Statistics and Data Mining

Overview of attention for book
Cover of 'Challenges in Computational Statistics and Data Mining'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Evolutionary Computation for Real-World Problems
  3. Altmetric Badge
    Chapter 2 Selection of Significant Features Using Monte Carlo Feature Selection
  4. Altmetric Badge
    Chapter 3 ADX Algorithm for Supervised Classification
  5. Altmetric Badge
    Chapter 4 Estimation of Entropy from Subword Complexity
  6. Altmetric Badge
    Chapter 5 Exact Rate of Convergence of Kernel-Based Classification Rule
  7. Altmetric Badge
    Chapter 6 Compound Bipolar Queries: A Step Towards an Enhanced Human Consistency and Human Friendliness
  8. Altmetric Badge
    Chapter 7 Process Inspection by Attributes Using Predicted Data
  9. Altmetric Badge
    Chapter 8 Székely Regularization for Uplift Modeling
  10. Altmetric Badge
    Chapter 9 Dominance-Based Rough Set Approach to Multiple Criteria Ranking with Sorting-Specific Preference Information
  11. Altmetric Badge
    Chapter 10 On Things Not Seen
  12. Altmetric Badge
    Chapter 11 Network Capacity Bound for Personalized Bipartite PageRank
  13. Altmetric Badge
    Chapter 12 Dependence Factor as a Rule Evaluation Measure
  14. Altmetric Badge
    Chapter 13 Recent Results on Nonparametric Quantile Estimation in a Simulation Model
  15. Altmetric Badge
    Chapter 14 Adaptive Monte Carlo Maximum Likelihood
  16. Altmetric Badge
    Chapter 15 What Do We Choose When We Err? Model Selection and Testing for Misspecified Logistic Regression Revisited
  17. Altmetric Badge
    Chapter 16 Semiparametric Inference in Identification of Block-Oriented Systems
  18. Altmetric Badge
    Chapter 17 Dealing with Data Difficulty Factors While Learning from Imbalanced Data
  19. Altmetric Badge
    Chapter 18 Personal Privacy Protection in Time of Big Data
  20. Altmetric Badge
    Chapter 19 Data Based Modeling
Overall attention for this book and its chapters
Altmetric Badge

Mentioned by

twitter
4 X users
googleplus
1 Google+ user

Citations

dimensions_citation
11 Dimensions

Readers on

mendeley
52 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
Challenges in Computational Statistics and Data Mining
Published by
Springer International Publishing, January 2016
DOI 10.1007/978-3-319-18781-5
ISBNs
978-3-31-918780-8, 978-3-31-918781-5
Authors

Stan Matwin, Jan Mielniczuk

Editors

Matwin, Stan, Mielniczuk, Jan

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 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 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 2%
France 1 2%
Unknown 50 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 23%
Student > Master 9 17%
Student > Bachelor 6 12%
Researcher 4 8%
Student > Doctoral Student 3 6%
Other 10 19%
Unknown 8 15%
Readers by discipline Count As %
Computer Science 19 37%
Engineering 6 12%
Social Sciences 3 6%
Business, Management and Accounting 3 6%
Mathematics 2 4%
Other 8 15%
Unknown 11 21%