Verfügbarkeit: Challenges in computational statistics and data mining

Challenges in computational statistics and data mining:

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Bibliographische Detailangaben
Weitere Verfasser:	Matwin, Stan 1949- (HerausgeberIn), Mielniczuk, Jan (HerausgeberIn)
Format:	Elektronisch E-Book
Sprache:	English
Veröffentlicht:	Cham Springer International Publishing [2016]
Schriftenreihe:	Studies in computational intelligence volume 605
Schlagworte:	Engineering Data mining Artificial intelligence Statistics Computational intelligence Computational Intelligence Data Mining and Knowledge Discovery Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences Artificial Intelligence (incl. Robotics) Ingenieurwissenschaften Künstliche Intelligenz Statistik Datenanalyse Data Mining Festschrift
Online-Zugang:	BTU01 FAB01 FAW01 FHA01 FHI01 FHN01 FHR01 FKE01 FRO01 FWS01 FWS02 UBY01 Volltext Inhaltsverzeichnis Abstract
Beschreibung:	1 Online Ressource (x, 399 p. 73 illus., 3 illus. in color)
ISBN:	9783319187815
DOI:	10.1007/978-3-319-18781-5

Internformat

MARC


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Datensatz im Suchindex

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adam_text	CHALLENGES IN COMPUTATIONAL STATISTICS AND DATA MINING / : 2016 TABLE OF CONTENTS / INHALTSVERZEICHNIS 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 SZEKELY 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 DIESES SCHRIFTSTUECK WURDE MASCHINELL ERZEUGT. CHALLENGES IN COMPUTATIONAL STATISTICS AND DATA MINING / : 2016 ABSTRACT / INHALTSTEXT 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 DIESES SCHRIFTSTUECK WURDE MASCHINELL ERZEUGT.
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spellingShingle	Challenges in computational statistics and data mining Studies in computational intelligence Engineering Data mining Artificial intelligence Statistics Computational intelligence Computational Intelligence Data Mining and Knowledge Discovery Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences Artificial Intelligence (incl. Robotics) Ingenieurwissenschaften Künstliche Intelligenz Statistik Datenanalyse (DE-588)4123037-1 gnd Data Mining (DE-588)4428654-5 gnd
subject_GND	(DE-588)4123037-1 (DE-588)4428654-5 (DE-588)4016928-5
title	Challenges in computational statistics and data mining
title_auth	Challenges in computational statistics and data mining
title_exact_search	Challenges in computational statistics and data mining
title_full	Challenges in computational statistics and data mining Stan Matwin, Jan Mielniczuk editors
title_fullStr	Challenges in computational statistics and data mining Stan Matwin, Jan Mielniczuk editors
title_full_unstemmed	Challenges in computational statistics and data mining Stan Matwin, Jan Mielniczuk editors
title_short	Challenges in computational statistics and data mining
title_sort	challenges in computational statistics and data mining
topic	Engineering Data mining Artificial intelligence Statistics Computational intelligence Computational Intelligence Data Mining and Knowledge Discovery Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences Artificial Intelligence (incl. Robotics) Ingenieurwissenschaften Künstliche Intelligenz Statistik Datenanalyse (DE-588)4123037-1 gnd Data Mining (DE-588)4428654-5 gnd
topic_facet	Engineering Data mining Artificial intelligence Statistics Computational intelligence Computational Intelligence Data Mining and Knowledge Discovery Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences Artificial Intelligence (incl. Robotics) Ingenieurwissenschaften Künstliche Intelligenz Statistik Datenanalyse Data Mining Festschrift
url	https://doi.org/10.1007/978-3-319-18781-5 http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028635086&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028635086&sequence=000003&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA
volume_link	(DE-604)BV020822171
work_keys_str_mv	AT matwinstan challengesincomputationalstatisticsanddatamining AT mielniczukjan challengesincomputationalstatisticsanddatamining

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