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    AN ADAPTIVE MULTI-LEVEL SEQUENTIAL FLOATING FEATURE SELECTION 

    Knitchepon Chotchantarakun; Knitchepon Chotchantarakun; Ohm Sornil; โอม ศรนิล; National Institute of Development Administration. School of Applied Statistics; Ohm Sornil; โอม ศรนิล (National Institute of Development Administration, 13/8/2021)

    Dealing with a large amount of available data becomes a major challenge in data mining and machine learning. Feature selection is a significant preprocessing step for selecting the most informative features by removing irrelevant and redundant features, especially for large datasets. These selected features play an important role in information searching and enhancing the performance of machine learning models such as classification and prediction. There have been several strategies proposed in the past few decades. In this dissertation, we ...