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  1. 1

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

    Udgivet 2010
    Thesis

    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 af Madarang, Jennelle Rizza M.

    Udgivet 2010
    Thesis

    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 af Mahinay, Kristine Karen C.

    Udgivet 2010
    Thesis

    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 af Parreño, Cherry Lyn N.

    Udgivet 2009
    Thesis

    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 af Ubas, Apple Grace Otero

    Udgivet 2008
    Thesis

    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 af Pelpinosas, Frank B.

    Udgivet 2008
    Thesis

    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 af Gabiana, Marie Lou Manalili

    Udgivet 2006
    Thesis

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

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