Näytetään 1 - 10 yhteensä 11 tuloksesta haulle '"Feature selection."', hakuaika: 0,02s Tarkenna hakua
  1. 1

    Modified principal feature analysis (MPFA) as a feature selection algorithm for clustering large data sets within missing values. Tekijä Aguelo, Renz Marion Y.

    Julkaistu 2010
    Opinnäyte

    Modified principal feature analysis (MPFA) as a feature selection algorithm for clustering large data sets within missing values.
  2. 2

    Clustering of datasets with missing values using principal feature analysis as a feature selection tool Tekijä Pelpinosas, Frank B.

    Julkaistu 2008
    Opinnäyte

    Clustering of datasets with missing values using principal feature analysis as a feature selection tool
  3. 3

    Learning to Decode Cognitive States from Brain Images. Tekijä Mitchell, Tom M.

    Julkaisussa Machine learning.
    Artikkeli

    Learning to Decode Cognitive States from Brain Images.
  4. 4

    Theoretical and empirical analysis of reliefF and rreliefF. Tekijä Robnik-Sikonja, Marko

    Julkaisussa Machine learning.
    Artikkeli

    Theoretical and empirical analysis of reliefF and rreliefF.
  5. 5

    Feature Weighting in k-Means Clustering. Tekijä Modha, Dharmendra S.

    Julkaisussa Machine learning.
    Artikkeli

    Feature Weighting in k-Means Clustering.
  6. 6

    Maximum Entropy Models with Inequality Constraints A Case Study on Text Categorization. Tekijä Kazama, Jun'ichi

    Julkaisussa Machine learning.
    Artikkeli

    Maximum Entropy Models with Inequality Constraints A Case Study on Text Categorization.
  7. 7

    Information mining over heterogeneous and high-dimensional time-series data in clinical trials databases. Tekijä Altiparmak, F.

    Artikkeli

    Information mining over heterogeneous and high-dimensional time-series data in clinical trials databases.
  8. 8

    The combined technique for detection of artifacts in clinical electroencephalograms of sleeping newborns. Tekijä Schetinin, V.

    Artikkeli

    The combined technique for detection of artifacts in clinical electroencephalograms of sleeping newborns.
  9. 9

    Local Dimensionality Reduction and Supervised Learning Within Natural Clusters for Biomedical Data Analysis. Tekijä Pechenizkiy, M.

    Artikkeli

    Local Dimensionality Reduction and Supervised Learning Within Natural Clusters for Biomedical Data Analysis.
  10. 10

    Fault location in electrical power systems using intelligent systems techniques. Tekijä Souza, J.C.S

    Artikkeli

    Fault location in electrical power systems using intelligent systems techniques.

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