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ORCIDNeurocomputing, Volume 343
Volume 343, May 2019
- Shuo Wang
, Leandro L. Minku, Nitesh V. Chawla, Xin Yao:
Learning in the presence of class imbalance and concept drift. 1-2 - Romero F. A. B. de Morais, Germano C. Vasconcelos:
Boosting the performance of over-sampling algorithms through under-sampling the minority class. 3-18 - Michal Koziarski, Bartosz Krawczyk, Michal Wozniak:
Radial-Based oversampling for noisy imbalanced data classification. 19-33 - Jayadeva, Himanshu Pant, Mayank Sharma, Sumit Soman:
Twin Neural Networks for the classification of large unbalanced datasets. 34-49 - Arya Iranmehr, Hamed Masnadi-Shirazi, Nuno Vasconcelos:
Cost-sensitive support vector machines. 50-64 - Kojo Sarfo Gyamfi, James Brusey, Andrew Hunt, Elena I. Gaura:
A dynamic linear model for heteroscedastic LDA under class imbalance. 65-75 - Paula Branco, Luís Torgo, Rita P. Ribeiro:
Pre-processing approaches for imbalanced distributions in regression. 76-99 - Santiago Egea Gómez, Luis Hernández-Callejo, Belén Carro Martínez, Antonio J. Sánchez-Esguevillas:
Exploratory study on Class Imbalance and solutions for Network Traffic Classification. 100-119 - Ruchika Malhotra, Shine Kamal:
An empirical study to investigate oversampling methods for improving software defect prediction using imbalanced data. 120-140 - Hualong Yu, Geoffrey I. Webb:
Adaptive online extreme learning machine by regulating forgetting factor by concept drift map. 141-153 - Haider Raza, Dheeraj Rathee, Shang-Ming Zhou, Hubert Cecotti, Girijesh Prasad:
Covariate shift estimation based adaptive ensemble learning for handling non-stationarity in motor imagery related EEG-based brain-computer interface. 154-166
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