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Improving accuracy of students' final grade prediction model using optimal equal width binning and synthetic minority over-sampling technique

Jishan, Syed; Rashu, Raisul; Haque, Naheena; Rahman, … - In: Decision Analytics 2 (2015) 1, pp. 1-25

-sampling technique known as the Synthetic Minority Over-Sampling (SMOTE) to improve the accuracy of the students' final grade prediction …

Persistent link: https://www.econbiz.de/10011656492

Improving accuracy of students' final grade prediction model using optimal equal width binning and synthetic minority over-sampling technique

Jishan, Syed; Rashu, Raisul; Haque, Naheena; Rahman, … - In: Decision Analytics 2 (2015), pp. 1-25

-sampling technique known as the Synthetic Minority Over-Sampling (SMOTE) to improve the accuracy of the students' final grade prediction …

Persistent link: https://www.econbiz.de/10010531019

Predicting the failures of prediction markets : a procedure of decision making using classification models

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Data imbalance in autism pre-diagnosis classification systems : an experimental study

Abdelhamid, Neda; Padmavathy, Arun; Peebles, David; … - In: Journal of information & knowledge management : JIKM 19 (2020) 1, pp. 2040014-1-2040014-16

Persistent link: https://www.econbiz.de/10012292628

Ensemble classifiers for bankruptcy prediction using SMOTE and RFECV

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Effects of resampling techniques on imbalanced data classification : a new under-resampling method

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Cluster based oversampling for imbalanced classification

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Imbalanced customer classification for bank direct marketing

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Grabit : gradient tree-boosted Tobit models for default prediction

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A comparison of resampling techniques for medical data using machine learning

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