Dimensionality reduction with unsupervised nearest neighbors:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Berlin
Springer
[2013]
|
| Schriftenreihe: | Intelligent systems reference library
volume 51 |
| Schlagworte: | |
| Online-Zugang: | BTU01 FHA01 FHI01 FHN01 FHR01 FKE01 FWS01 UBY01 Volltext Inhaltsverzeichnis Abstract |
| Beschreibung: | 1 Online Ressource (XII, 132 p. 48 illus., 45 illus. in color) |
| ISBN: | 9783642386527 |
| DOI: | 10.1007/978-3-642-38652-7 |
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| adam_text | DIMENSIONALITY REDUCTION WITH UNSUPERVISED NEAREST NEIGHBORS
/ KRAMER, OLIVER
: 2013
TABLE OF CONTENTS / INHALTSVERZEICHNIS
PART I FOUNDATIONS
PART II UNSUPERVISED NEAREST NEIGHBORS
PART III CONCLUSIONS
DIESES SCHRIFTSTUECK WURDE MASCHINELL ERZEUGT.
DIMENSIONALITY REDUCTION WITH UNSUPERVISED NEAREST NEIGHBORS
/ KRAMER, OLIVER
: 2013
ABSTRACT / INHALTSTEXT
THIS BOOK IS DEVOTED TO A NOVEL APPROACH FOR DIMENSIONALITY REDUCTION
BASED ON THE FAMOUS NEAREST NEIGHBOR METHOD THAT IS A POWERFUL
CLASSIFICATION AND REGRESSION APPROACH. IT STARTS WITH AN INTRODUCTION
TO MACHINE LEARNING CONCEPTS AND A REAL-WORLD APPLICATION FROM THE
ENERGY DOMAIN. THEN, UNSUPERVISED NEAREST NEIGHBORS (UNN) IS INTRODUCED
AS EFFICIENT ITERATIVE METHOD FOR DIMENSIONALITY REDUCTION. VARIOUS UNN
MODELS ARE DEVELOPED STEP BY STEP, REACHING FROM A SIMPLE ITERATIVE
STRATEGY FOR DISCRETE LATENT SPACES TO A STOCHASTIC KERNEL-BASED
ALGORITHM FOR LEARNING SUBMANIFOLDS WITH INDEPENDENT PARAMETERIZATIONS.
EXTENSIONS THAT ALLOW THE EMBEDDING OF INCOMPLETE AND NOISY PATTERNS ARE
INTRODUCED. VARIOUS OPTIMIZATION APPROACHES ARE COMPARED, FROM
EVOLUTIONARY TO SWARM-BASED HEURISTICS. EXPERIMENTAL COMPARISONS TO
RELATED METHODOLOGIES TAKING INTO ACCOUNT ARTIFICIAL TEST DATA SETS AND
ALSO REAL-WORLD DATA DEMONSTRATE THE BEHAVIOR OF UNN IN PRACTICAL
SCENARIOS. THE BOOK CONTAINS NUMEROUS COLOR FIGURES TO ILLUSTRATE THE
INTRODUCED CONCEPTS AND TO HIGHLIGHT THE EXPERIMENTAL RESULTS.
DIESES SCHRIFTSTUECK WURDE MASCHINELL ERZEUGT.
|
| any_adam_object | 1 |
| author | Kramer, Oliver |
| author_facet | Kramer, Oliver |
| author_role | aut |
| author_sort | Kramer, Oliver |
| author_variant | o k ok |
| building | Verbundindex |
| bvnumber | BV043209953 |
| classification_rvk | ST 530 |
| collection | ZDB-2-ENG |
| ctrlnum | (OCoLC)852532564 (DE-599)BVBBV043209953 |
| dewey-full | 519 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 519 - Probabilities and applied mathematics |
| dewey-raw | 519 |
| dewey-search | 519 |
| dewey-sort | 3519 |
| dewey-tens | 510 - Mathematics |
| discipline | Informatik Mathematik |
| doi_str_mv | 10.1007/978-3-642-38652-7 |
| format | Electronic eBook |
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| id | DE-604.BV043209953 |
| illustrated | Not Illustrated |
| indexdate | 2024-08-01T16:14:46Z |
| institution | BVB |
| isbn | 9783642386527 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-028633114 |
| oclc_num | 852532564 |
| open_access_boolean | |
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| owner_facet | DE-Aug4 DE-898 DE-BY-UBR DE-573 DE-859 DE-634 DE-92 DE-706 DE-863 DE-BY-FWS |
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| psigel | ZDB-2-ENG ZDB-2-ENG_2013 |
| publishDate | 2013 |
| publishDateSearch | 2013 |
| publishDateSort | 2013 |
| publisher | Springer |
| record_format | marc |
| series | Intelligent systems reference library |
| series2 | Intelligent systems reference library |
| spellingShingle | Kramer, Oliver Dimensionality reduction with unsupervised nearest neighbors Intelligent systems reference library Engineering Operations research Decision making Artificial intelligence Applied mathematics Engineering mathematics Appl.Mathematics/Computational Methods of Engineering Artificial Intelligence (incl. Robotics) Operation Research/Decision Theory Ingenieurwissenschaften Künstliche Intelligenz Maschinelles Lernen (DE-588)4193754-5 gnd Data Mining (DE-588)4428654-5 gnd Dimensionsreduktion (DE-588)4224279-4 gnd Nächste-Nachbarn-Problem (DE-588)4376579-8 gnd Datenanalyse (DE-588)4123037-1 gnd |
| subject_GND | (DE-588)4193754-5 (DE-588)4428654-5 (DE-588)4224279-4 (DE-588)4376579-8 (DE-588)4123037-1 |
| title | Dimensionality reduction with unsupervised nearest neighbors |
| title_auth | Dimensionality reduction with unsupervised nearest neighbors |
| title_exact_search | Dimensionality reduction with unsupervised nearest neighbors |
| title_full | Dimensionality reduction with unsupervised nearest neighbors Oliver Kramer |
| title_fullStr | Dimensionality reduction with unsupervised nearest neighbors Oliver Kramer |
| title_full_unstemmed | Dimensionality reduction with unsupervised nearest neighbors Oliver Kramer |
| title_short | Dimensionality reduction with unsupervised nearest neighbors |
| title_sort | dimensionality reduction with unsupervised nearest neighbors |
| topic | Engineering Operations research Decision making Artificial intelligence Applied mathematics Engineering mathematics Appl.Mathematics/Computational Methods of Engineering Artificial Intelligence (incl. Robotics) Operation Research/Decision Theory Ingenieurwissenschaften Künstliche Intelligenz Maschinelles Lernen (DE-588)4193754-5 gnd Data Mining (DE-588)4428654-5 gnd Dimensionsreduktion (DE-588)4224279-4 gnd Nächste-Nachbarn-Problem (DE-588)4376579-8 gnd Datenanalyse (DE-588)4123037-1 gnd |
| topic_facet | Engineering Operations research Decision making Artificial intelligence Applied mathematics Engineering mathematics Appl.Mathematics/Computational Methods of Engineering Artificial Intelligence (incl. Robotics) Operation Research/Decision Theory Ingenieurwissenschaften Künstliche Intelligenz Maschinelles Lernen Data Mining Dimensionsreduktion Nächste-Nachbarn-Problem Datenanalyse |
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