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  "Title": "Asymptotically Bias-Corrected Regularized Linear Discriminant\nAnalysis",
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  "Author": "Dmitriy Fedorov [aut, cre], Amin Zollanvari [aut], Aresh\nDadlani [aut], Berdakh Abibullaev [aut]",
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  "Description": "Offers methods to perform asymptotically bias-corrected\nregularized linear discriminant analysis (ABC_RLDA) for\ncost-sensitive binary classification. The bias-correction is an\nestimate of the bias term added to regularized discriminant\nanalysis (RLDA) that minimizes the overall risk. The default\nmagnitude of misclassification costs are equal and set to 0.5;\nhowever, the package also offers the options to set them to\nsome predetermined values or, alternatively, take them as\nhyperparameters to tune. A. Zollanvari, M. Abdirash, A. Dadlani\nand B. Abibullaev (2019) <doi:10.1109/LSP.2019.2918485>.",
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  "Date/Publication": "2020-05-28 03:20:02 UTC",
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