Christos K. Aridas
Christos K. Aridas
Computational Intelligence Laboratory, Department of Mathematics, University of Patras, Greece
Verified email at upatras.gr
Title
Cited by
Cited by
Year
Imbalanced-learn: A Python Toolbox to Tackle the Curse of Imbalanced Datasets in Machine Learning
G Lemaitre, F Nogueira, CK Aridas
Journal of Machine Learning Research 18 (17), 1-5, 2017
9022017
Multi-Objective Evolutionary Optimization Algorithms for Machine Learning: A Recent Survey
SAN Alexandropoulos, CK Aridas, SB Kotsiantis, MN Vrahatis
Springer Optimization and Its Applications 145, 35-55, 2019
192019
Uncertainty based under-sampling for learning Naive Bayes classifiers under imbalanced data sets
CK Aridas, S Karlos, VG Kanas, N Fazakis, SB Kotsiantis
IEEE Access, 2020
122020
A Deep Dense Neural Network for Bankruptcy Prediction
SAN Alexandropoulos, CK Aridas, SB Kotsiantis, MN Vrahatis
International Conference on Engineering Applications of Neural Networks, 435-444, 2019
72019
Combining Active Learning with Self-train algorithm for classification of multimodal problems
S Karlos, VG Kanas, C Aridas, N Fazakis, S Kotsiantis
2019 10th International Conference on Information, Intelligence, Systems and …, 2019
62019
Combination of Active Learning and Semi-Supervised Learning under a Self-Training Scheme
N Fazakis, VG Kanas, CK Aridas, S Karlos, S Kotsiantis
Entropy 21 (10), 988, 2019
52019
Stacking Strong Ensembles of Classifiers
SAN Alexandropoulos, CK Aridas, SB Kotsiantis, MN Vrahatis
IFIP International Conference on Artificial Intelligence Applications and …, 2019
52019
Combining random forest and support vector machines for semi-supervised learning
C Aridas, S Kotsiantis
Proceedings of the 19th Panhellenic Conference on Informatics, 123-128, 2015
52015
Random resampling in the one-versus-all strategy for handling multi-class problems
CK Aridas, SAN Alexandropoulos, SB Kotsiantis, MN Vrahatis
International Conference on Engineering Applications of Neural Networks, 111-121, 2017
42017
Increasing Diversity in Random Forests Using Naive Bayes
CK Aridas, SB Kotsiantis, MN Vrahatis
IFIP International Conference on Artificial Intelligence Applications and …, 2016
42016
Hybrid local boosting utilizing unlabeled data in classification tasks
CK Aridas, SB Kotsiantis, MN Vrahatis
Evolving Systems 10 (1), 51-61, 2017
32017
Combining prototype selection with local boosting
CK Aridas, SB Kotsiantis, MN Vrahatis
IFIP International Conference on Artificial Intelligence Applications and …, 2016
32016
Investigating the Benefits of Exploiting Incremental Learners Under Active Learning Scheme
S Karlos, VG Kanas, N Fazakis, C Aridas, S Kotsiantis
IFIP International Conference on Artificial Intelligence Applications and …, 2019
22019
Imbalanced dataset for benchmarking
G Lemaitre, F Nogueira, CK Aridas, DVR Oliveira
Zenodo, 2016
22016
A tool supported framework for the assessment of algorithmic accountability
E Tagiou, Y Kanellopoulos, C Aridas, C Makris
2019 10th International Conference on Information, Intelligence, Systems and …, 2019
12019
Classification of acoustical signals by combining active learning strategies with semi-supervised learning schemes
S Karlos, C Aridas, VG Kanas, S Kotsiantis
Neural Computing and Applications, 1-18, 2021
2021
PyThia: A Reporting Tool on Bias Evaluation and Mitigation
Y Kanellopoulos, C Aridas
4th Workshop on Mechanism Design for Social, 2020
2020
vfi: Classification by Voting Feature Intervals in Python
CK Aridas
Zenodo, 2020
2020
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