Verfügbarkeit: Unsupervised learning algorithms

Unsupervised learning algorithms:

Gespeichert in:

Bibliographische Detailangaben
Weitere Verfasser:	Celebi, M. Emre (HerausgeberIn), Aydin, Kemal (HerausgeberIn)
Format:	Elektronisch E-Book
Sprache:	English
Veröffentlicht:	Cham Springer International Publishing [2016]
Schlagworte:	Engineering Computer communication systems Data mining Artificial intelligence Pattern recognition Computational intelligence Electrical engineering Communications Engineering, Networks Computational Intelligence Computer Communication Networks Pattern Recognition Artificial Intelligence (incl. Robotics) Data Mining and Knowledge Discovery Ingenieurwissenschaften Künstliche Intelligenz
Online-Zugang:	BTU01 FAB01 FAW01 FHA01 FHI01 FHN01 FHR01 FKE01 FRO01 FWS01 FWS02 TUM01 UBY01 Volltext Inhaltsverzeichnis Abstract
Beschreibung:	1 Online-Ressource (x, 558 p. 160 illus., 101 illus. in color)
ISBN:	9783319242118 9783319242095
DOI:	10.1007/978-3-319-24211-8

Internformat

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Datensatz im Suchindex

DE-BY-FWS_katkey	617233
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adam_text	UNSUPERVISED LEARNING ALGORITHMS / : 2016 TABLE OF CONTENTS / INHALTSVERZEICHNIS INTRODUCTION FEATURE CONSTRUCTION FEATURE EXTRACTION FEATURE SELECTION ASSOCIATION RULE LEARNING CLUSTERING ANOMALY/NOVELTY/OUTLIER DETECTION EVALUATION OF UNSUPERVISED LEARNING APPLICATIONS CONCLUSION DIESES SCHRIFTSTUECK WURDE MASCHINELL ERZEUGT. UNSUPERVISED LEARNING ALGORITHMS / : 2016 ABSTRACT / INHALTSTEXT THIS BOOK SUMMARIZES THE STATE-OF-THE-ART IN UNSUPERVISED LEARNING. THE CONTRIBUTORS DISCUSS HOW WITHTHE PROLIFERATION OF MASSIVE AMOUNTS OF UNLABELED DATA, UNSUPERVISED LEARNING ALGORITHMS, WHICH CAN AUTOMATICALLY DISCOVER INTERESTING AND USEFUL PATTERNS IN SUCH DATA, HAVE GAINED POPULARITY AMONG RESEARCHERS AND PRACTITIONERS. THE AUTHORS OUTLINE HOW THESE ALGORITHMS HAVE FOUND NUMEROUS APPLICATIONS INCLUDING PATTERN RECOGNITION, MARKET BASKET ANALYSIS, WEB MINING, SOCIAL NETWORK ANALYSIS, INFORMATION RETRIEVAL, RECOMMENDER SYSTEMS, MARKET RESEARCH, INTRUSION DETECTION, AND FRAUD DETECTION. THEY PRESENT HOW THE DIFFICULTY OF DEVELOPING THEORETICALLY SOUND APPROACHES THAT ARE AMENABLE TO OBJECTIVE EVALUATION HAVE RESULTED IN THE PROPOSAL OF NUMEROUS UNSUPERVISED LEARNING ALGORITHMS OVER THE PAST HALF-CENTURY. THE INTENDED AUDIENCE INCLUDES RESEARCHERS AND PRACTITIONERS WHO ARE INCREASINGLY USING UNSUPERVISED LEARNING ALGORITHMS TO ANALYZE THEIR DATA. TOPICS OF INTEREST INCLUDE ANOMALY DETECTION, CLUSTERING, FEATURE EXTRACTION, AND APPLICATIONS OF UNSUPERVISED LEARNING. EACH CHAPTER IS CONTRIBUTED BY A LEADING EXPERT IN THE FIELD DIESES SCHRIFTSTUECK WURDE MASCHINELL ERZEUGT.
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discipline	Informatik Elektrotechnik Elektrotechnik / Elektronik / Nachrichtentechnik Maschinenbau
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spellingShingle	Unsupervised learning algorithms Engineering Computer communication systems Data mining Artificial intelligence Pattern recognition Computational intelligence Electrical engineering Communications Engineering, Networks Computational Intelligence Computer Communication Networks Pattern Recognition Artificial Intelligence (incl. Robotics) Data Mining and Knowledge Discovery Ingenieurwissenschaften Künstliche Intelligenz
title	Unsupervised learning algorithms
title_auth	Unsupervised learning algorithms
title_exact_search	Unsupervised learning algorithms
title_full	Unsupervised learning algorithms M. Emre Celebi, Kemal Aydin editors
title_fullStr	Unsupervised learning algorithms M. Emre Celebi, Kemal Aydin editors
title_full_unstemmed	Unsupervised learning algorithms M. Emre Celebi, Kemal Aydin editors
title_short	Unsupervised learning algorithms
title_sort	unsupervised learning algorithms
topic	Engineering Computer communication systems Data mining Artificial intelligence Pattern recognition Computational intelligence Electrical engineering Communications Engineering, Networks Computational Intelligence Computer Communication Networks Pattern Recognition Artificial Intelligence (incl. Robotics) Data Mining and Knowledge Discovery Ingenieurwissenschaften Künstliche Intelligenz
topic_facet	Engineering Computer communication systems Data mining Artificial intelligence Pattern recognition Computational intelligence Electrical engineering Communications Engineering, Networks Computational Intelligence Computer Communication Networks Pattern Recognition Artificial Intelligence (incl. Robotics) Data Mining and Knowledge Discovery Ingenieurwissenschaften Künstliche Intelligenz
url	https://doi.org/10.1007/978-3-319-24211-8 http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028961798&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=028961798&sequence=000003&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA
work_keys_str_mv	AT celebimemre unsupervisedlearningalgorithms AT aydinkemal unsupervisedlearningalgorithms

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