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Visualization and interactive feature selection for unsupervised data

Authors:

Jennifer G. Dy,

Carla E. BrodleyAuthors Info & Claims

KDD '00: Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining

Pages 360 - 364

https://doi.org/10.1145/347090.347168

Published: 01 August 2000 Publication History

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Cited By

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Theissler AThomas MBurch MGerschner F(2022)ConfusionVisKnowledge-Based Systems10.1016/j.knosys.2022.108651247:COnline publication date: 8-Jul-2022
https://dl.acm.org/doi/10.1016/j.knosys.2022.108651
Grimmeisen BChegini MTheissler A(2022)VisGIL: machine learning-based visual guidance for interactive labelingThe Visual Computer10.1007/s00371-022-02648-239:10(5097-5119)Online publication date: 25-Sep-2022
https://doi.org/10.1007/s00371-022-02648-2
Fezer ERaab DTheissler ABurch MWestenberg MNguyen QZhao Y(2020)XplainableClusterExplorerProceedings of the 13th International Symposium on Visual Information Communication and Interaction10.1145/3430036.3430066(1-5)Online publication date: 8-Dec-2020
https://dl.acm.org/doi/10.1145/3430036.3430066
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Index Terms

Visualization and interactive feature selection for unsupervised data
1. Computing methodologies
  1. Machine learning
    1. Learning paradigms
      1. Unsupervised learning
        Cluster analysis
    2. Machine learning algorithms
      1. Feature selection
2. Information systems
  1. Information retrieval
    1. Information retrieval query processing
    2. Retrieval tasks and goals
      1. Clustering and classification
  2. Information systems applications
    1. Data mining
      1. Clustering

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Published In

KDD '00: Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining

August 2000

537 pages

ISBN:1581132336

DOI:10.1145/347090

Chairmen:
Raghu Ramakrishnan
Univ. of Wisconsin
,
Sal Stolfo
Columbia Univ., New York, NY
,
Roberto Bayardo
IBM Almaden Research Center, San Jose, CA
,
Ismail Parsa
Epsilon

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 August 2000

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Sponsor:

KDD00: The Second Annual International Conference on Knowledge Discovery in Data

August 20 - 23, 2000

Massachusetts, Boston, USA

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Overall Acceptance Rate 1,133 of 8,635 submissions, 13%

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Cited By

View all

Theissler AThomas MBurch MGerschner F(2022)ConfusionVisKnowledge-Based Systems10.1016/j.knosys.2022.108651247:COnline publication date: 8-Jul-2022
https://dl.acm.org/doi/10.1016/j.knosys.2022.108651
Grimmeisen BChegini MTheissler A(2022)VisGIL: machine learning-based visual guidance for interactive labelingThe Visual Computer10.1007/s00371-022-02648-239:10(5097-5119)Online publication date: 25-Sep-2022
https://doi.org/10.1007/s00371-022-02648-2
Fezer ERaab DTheissler ABurch MWestenberg MNguyen QZhao Y(2020)XplainableClusterExplorerProceedings of the 13th International Symposium on Visual Information Communication and Interaction10.1145/3430036.3430066(1-5)Online publication date: 8-Dec-2020
https://dl.acm.org/doi/10.1145/3430036.3430066
Bau DLiu SWang TZhu JTorralba A(2020)Rewriting a Deep Generative ModelComputer Vision – ECCV 202010.1007/978-3-030-58452-8_21(351-369)Online publication date: 3-Nov-2020
https://doi.org/10.1007/978-3-030-58452-8_21
Snyder LLin YKarimzadeh MGoldwasser DEbert D(2019)Interactive Learning for Identifying Relevant Tweets to Support Real-time Situational AwarenessIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2019.2934614(1-1)Online publication date: 2019
https://doi.org/10.1109/TVCG.2019.2934614
Artur EMinghim R(2019)A novel visual approach for enhanced attribute analysis and selectionComputers and Graphics10.1016/j.cag.2019.08.01584:C(160-172)Online publication date: 1-Nov-2019
https://dl.acm.org/doi/10.1016/j.cag.2019.08.015
Dash MKoot P(2018)Feature Selection for ClusteringEncyclopedia of Database Systems10.1007/978-1-4614-8265-9_613(1459-1466)Online publication date: 7-Dec-2018
https://doi.org/10.1007/978-1-4614-8265-9_613
Ye XSakurai T(2017)Unsupervised Feature Learning for Gene Selection in Microarray Data AnalysisProceedings of the 1st International Conference on Medical and Health Informatics 201710.1145/3107514.3107527(101-106)Online publication date: 20-May-2017
https://dl.acm.org/doi/10.1145/3107514.3107527
Dash MKoot P(2017)Feature Selection for ClusteringEncyclopedia of Database Systems10.1007/978-1-4899-7993-3_613-2(1-8)Online publication date: 18-Jan-2017
https://doi.org/10.1007/978-1-4899-7993-3_613-2
Hoseini EMansoori E(2016)An unsupervised approach for feature selection in linked data2016 24th Iranian Conference on Electrical Engineering (ICEE)10.1109/IranianCEE.2016.7585828(1881-1886)Online publication date: May-2016
https://doi.org/10.1109/IranianCEE.2016.7585828
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