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Improving biometric recognition by means of score ratio, the likelihood ratio for non-probabilistic classifiers. A benchmarking study.

, , and . IET Biom., 10 (2): 127-141 (2021)

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On the Use of Score Ratio with Distance-Based Classifiers in Biometric Signature Recognition., , and . ICONIP (1), volume 9489 of Lecture Notes in Computer Science, page 318-327. Springer, (2015)The pedagogical model of SIAL: an adaptive and open-ended intelligent tutoring system for first order logic., and . ITiCSE, page 21-26. ACM, (2018)Improving biometric recognition by means of score ratio, the likelihood ratio for non-probabilistic classifiers. A benchmarking study., , and . IET Biom., 10 (2): 127-141 (2021)Client threshold prediction in biometric signature recognition by means of Multiple Linear Regression and its use for score normalization., , , and . Pattern Recognition, (2016)Learner-Adaptive Pedagogical Model in SIAL, an Open-Ended Intelligent Tutoring System for First Order Logic., and . AIED, volume 9112 of Lecture Notes in Computer Science, page 702-705. Springer, (2015)Microarray gene expression classification with few genes: Criteria to combine attribute selection and classification methods., , , and . Expert Syst. Appl., 39 (8): 7270-7280 (2012)A New Methodology for Feature Selection Based on Machine Learning Methods Applied to Glaucoma., , , and . IWANN (1), volume 5517 of Lecture Notes in Computer Science, page 1037-1044. Springer, (2009)A New Proposal for Score Normalization in Biometric Signature Recognition Based on Client Threshold Prediction., , , and . ICDM, page 1128-1133. IEEE Computer Society, (2012)Improving ANN performance for imbalanced data sets by means of the NTIL technique., and . IJCNN, page 1-6. IEEE, (2010)A New Approach for a Priori Client Threshold Estimation in Biometric Signature Recognition Based on Multiple Linear Regression., , , and . ICONIP (3), volume 7665 of Lecture Notes in Computer Science, page 174-182. Springer, (2012)