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  1. 1

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

    Publié 2010
    Thèse

    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 par Madarang, Jennelle Rizza M.

    Publié 2010
    Thèse

    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 par Mahinay, Kristine Karen C.

    Publié 2010
    Thèse

    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 par Parreño, Cherry Lyn N.

    Publié 2009
    Thèse

    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 par Ubas, Apple Grace Otero

    Publié 2008
    Thèse

    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 par Pelpinosas, Frank B.

    Publié 2008
    Thèse

    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 par Gabiana, Marie Lou Manalili

    Publié 2006
    Thèse

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

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