Challenges in Computational Statistics and Data Mining (Studies in Computational Intelligence, 605)

ISBN 10: 3319187805 / ISBN 13: 9783319187808

Edité par Springer, 2015

A propos de cet article

N° de réf. du vendeur I-9783319187808

Détails bibliographiques

• Titre: Challenges in Computational Statistics and Data Mining (Studies in Computational Intelligence, 605)
• Éditeur: Springer
• Date de parution: 2015
• Langue: anglais
• ISBN à 10 chiffres: 3319187805
• ISBN à 13 chiffres: 9783319187808
• Reliure: Couverture rigide
• État de l'article: New

A propos de ce titre

Synopsis

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.