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  1. 1

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

    Publicado 2010
    Tesis

    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 por Madarang, Jennelle Rizza M.

    Publicado 2010
    Tesis

    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 por Mahinay, Kristine Karen C.

    Publicado 2010
    Tesis

    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 por Parreño, Cherry Lyn N.

    Publicado 2009
    Tesis

    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 por Ubas, Apple Grace Otero

    Publicado 2008
    Tesis

    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 por Pelpinosas, Frank B.

    Publicado 2008
    Tesis

    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 por Gabiana, Marie Lou Manalili

    Publicado 2006
    Tesis

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

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