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Probabilistic Diagnostic Model for Handling Classifier Degradation in Machine Learning
2019Several studies point out different causes of performance degradation in supervised machine learning. Problems such as class imbalance, overlapping, small-disjuncts, noisy labels, and sparseness limit accuracy in classification algorithms. Even though a number of approaches either in the form of a methodology or an algorithm try to minimize performance
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Handling Data Imbalance Using Text Augmentation For Classifying Public Complaints
2023 International Conference on Computer, Control, Informatics and its Applications (IC3INA), 2023Muhammad Rizqi Indrahimawan +2 more
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Handling CHD Classifier Based on Machine Learning and Fuzzy Logic Techniques
2023 10th IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON), 2023Shashi Kant +2 more
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Combination of Classifiers With Optimal Weight Based on Evidential Reasoning
IEEE Transactions on Fuzzy Systems, 2018Zhun-Ga Liu, Jean Dezert
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An experimental comparison of ensemble of classifiers for bankruptcy prediction and credit scoring
Expert Systems With Applications, 2009Loris Nanni, Alessandra Lumini
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Comprehensive evaluation of twin SVM based classifiers on UCI datasets
Applied Soft Computing Journal, 2019Mohammad Tanveer +2 more
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