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      DETECTION OF THE RED PALM WEEVIL RHYNCHOPHORUS FERRUGINEUSUSING ITS BIOACOUSTICS FEATURES

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      Bioacoustics
      Informa UK Limited

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          Feature selection based on mutual information: criteria of max-dependency, max-relevance, and min-redundancy.

          Feature selection is an important problem for pattern classification systems. We study how to select good features according to the maximal statistical dependency criterion based on mutual information. Because of the difficulty in directly implementing the maximal dependency condition, we first derive an equivalent form, called minimal-redundancy-maximal-relevance criterion (mRMR), for first-order incremental feature selection. Then, we present a two-stage feature selection algorithm by combining mRMR and other more sophisticated feature selectors (e.g., wrappers). This allows us to select a compact set of superior features at very low cost. We perform extensive experimental comparison of our algorithm and other methods using three different classifiers (naive Bayes, support vector machine, and linear discriminate analysis) and four different data sets (handwritten digits, arrhythmia, NCI cancer cell lines, and lymphoma tissues). The results confirm that mRMR leads to promising improvement on feature selection and classification accuracy.
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            Eavesdropping on Insects Hidden in Soil and Interior Structures of Plants

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              Development of a Pheromone-Based Trapping System for Rhynchophorus palmarum (Coleoptera: Curculionidae)

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                Author and article information

                Journal
                Bioacoustics
                Bioacoustics
                Informa UK Limited
                0952-4622
                2165-0586
                January 2010
                January 2010
                : 19
                : 3
                : 177-194
                Article
                10.1080/09524622.2010.9753623
                67dc4a23-ea2a-411f-9c14-27afc1c01bf3
                © 2010
                History

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