Challenges in Computational Statistics and Data Mining

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Details

This volume contains nineteen research papers belonging to the

areas of computational statistics, data mining, and their applications. Those papers, all written specifically for this volume, are their authors' contributions to honour and celebrate Professor Jacek Koronacki on the occcasion of his 70th birthday. The

book's related and often interconnected topics, represent Jacek Koronacki's research interests and their evolution. They also clearly indicate how close the areas of computational statistics and data mining are.


Presents recent Challenges in Computational Statistics and Data Mining Honorary book for Professor Jacek Koronacki on the occasion of his 70th birthday Demonstrates close connection between the areas of computational statistics and data mining and their applications Includes supplementary material: sn.pub/extras

Klappentext

This volume contains nineteen research papers belonging to the

areas of computational statistics, data mining, and their applications. Those papers, all written specifically for this volume, are their authors' contributions to honour and celebrate Professor Jacek Koronacki on the occcasion of his 70th birthday. The

book's related and often interconnected topics, represent Jacek Koronacki's research interests and their evolution. They also clearly indicate how close the areas of computational statistics and data mining are.


Inhalt

Evolutionary Computation for Real-world Problems.- Selection of Significant Features Using Monte Carlo Feature Selection.- ADX Algorithm for Supervised Classification.- Estimation of Entropy from Subword Complexity.- Exact Rates of Convergence of Kernel-based Classification Rule.- Compound Bipolar Queries: a Step Towards an Enhanced Human Consistency and Human Friendliness.- Process Inspection by Attributes Using Predicted Data.- Székely Regularization for Uplift Modeling.- Dominance-Based Rough Set Approach to Multiple Criterion Ranking with Sorting-specific Preference Information.- On things not Seen.- Network Capacity Bound for Personalized Bipartite Page Rank.- Dependence Factor as a Rule Evaluation Measure.- Recent Results on Quantlie Estimation Methods in Simulation Model.- Adaptive Monte Carlo Maximum Likelihood.- What Do we Choose when we Err? Model Selection and Testing for Misspecified Logistic Regression Revisited.- Semiparametric Inference Identification of Block-oriented Systems.- Dealing with Data Difficulty Factors While Learning from Imbalanced Data.- Privacy Protection in a Time of Big Data.- Data Based Modeling.

Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09783319370088
    • Genre Technology Encyclopedias
    • Auflage Softcover reprint of the original 1st edition 2016
    • Editor Jan Mielniczuk, Stan Matwin
    • Lesemotiv Verstehen
    • Anzahl Seiten 412
    • Herausgeber Springer International Publishing
    • Größe H235mm x B155mm x T23mm
    • Jahr 2016
    • EAN 9783319370088
    • Format Kartonierter Einband
    • ISBN 3319370081
    • Veröffentlichung 15.10.2016
    • Titel Challenges in Computational Statistics and Data Mining
    • Untertitel Studies in Computational Intelligence 605
    • Gewicht 622g
    • Sprache Englisch

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