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- W2291879968 abstract "Process with high dimensional data is enormous issue in data mining and machine learning applications. Feature selection is the mode of recognize the good number of features that produce well-suited outcome as the unique entire set of features. Feature selection process constructs a pathway to reduce the dimensionality and time complexity and also improve the accuracy level of classifier. In this paper, we use an alternative approach, called affinity propagation algorithm for effective and efficient feature selection and clustering process. The endeavor is to improve the performance in terms accuracy and time complexity." @default.
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- W2291879968 date "2014-08-02" @default.
- W2291879968 modified "2023-09-25" @default.
- W2291879968 title "EFFICIENT AND EFFECTIVE SUBSET SELECTION PROCESS BASED ON CLUSTERING ALGORITHM" @default.
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