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  1. 1

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

    Wydane 2010
    Praca dyplomowa

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

    Modified K-mean clustering algorithm for fixed numeric and categorical data sets with missing values od Madarang, Jennelle Rizza M.

    Wydane 2010
    Praca dyplomowa

    Modified K-mean clustering algorithm for fixed numeric and categorical data sets with missing values
  3. 3

    Exploratory analysis on DPCoA on small data sets with missing values using imputation methods od Mahinay, Kristine Karen C.

    Wydane 2010
    Praca dyplomowa

    Exploratory analysis on DPCoA on small data sets with missing values using imputation methods
  4. 4

    Data Clustering system on categorical data using modified K-modes clustering algorithms od Parreño, Cherry Lyn N.

    Wydane 2009
    Praca dyplomowa

    Data Clustering system on categorical data using modified K-modes clustering algorithms
  5. 5

    Fuzzy Jaccard similarity approach in handling missing values for randomly amplified polymorphic DNA (RAPD) analysis od Ubas, Apple Grace Otero

    Wydane 2008
    Praca dyplomowa

    Fuzzy Jaccard similarity approach in handling missing values for randomly amplified polymorphic DNA (RAPD) analysis
  6. 6

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

    Wydane 2008
    Praca dyplomowa

    Clustering of datasets with missing values using principal feature analysis as a feature selection tool
  7. 7

    A modified K-modes algorithm for clustering categorical data sets with missing values using bhattacharyya distance function od Gabiana, Marie Lou Manalili

    Wydane 2006
    Praca dyplomowa

    A modified K-modes algorithm for clustering categorical data sets with missing values using bhattacharyya distance function

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