Outputs (3)

Response to discussion on “Improved overlap-based undersampling for imbalanced dataset classification with application to epilepsy and Parkinson’s disease.” (2020)
Journal Article
VUTTIPITTAYAMONGKOL, P. and ELYAN, E. 2020. Response to discussion on “Improved overlap-based undersampling for imbalanced dataset classification with application to epilepsy and Parkinson’s disease.”. International journal of neural systems [online], 30(9), article ID 2075002. Available from: https://doi.org/10.1142/s0129065720750027

In the paper 'Improved Overlap-Based Undersampling for Imbalanced Dataset Classification with Application to Epilepsy and Parkinson's Disease', the authors introduced two new methods that address the class overlap problem in imbalanced datasets. The... Read More about Response to discussion on “Improved overlap-based undersampling for imbalanced dataset classification with application to epilepsy and Parkinson’s disease.”.

Improved overlap-based undersampling for imbalanced dataset classification with application to epilepsy and Parkinson's disease. (2020)
Journal Article
VUTTIPITTAYAMONGKOL, P. and ELYAN, E. 2020. Improved overlap-based undersampling for imbalanced dataset classification with application to epilepsy and Parkinson's disease. International journal of neural systems [online], 30(8), article ID 2050043. Available from: https://doi.org/10.1142/S0129065720500434

Classification of imbalanced datasets has attracted substantial research interest over the past decades. Imbalanced datasets are common in several domains such as health, finance, security and others. A wide range of solutions to handle imbalanced da... Read More about Improved overlap-based undersampling for imbalanced dataset classification with application to epilepsy and Parkinson's disease..

Overlap-based undersampling method for classification of imbalanced medical datasets. (2020)
Presentation / Conference Contribution
VUTTIPITTAYAMONGKOL, P. and ELYAN, E. 2020. Overlap-based undersampling method for classification of imbalanced medical datasets. In Maglogiannis, I., Iliadis, L. and Pimenidis, E. (eds.) Artificial intelligence applications and innovations: AIAI 2020; proceedings of 16th International Federation for Information Processing working group (IFIP WG) 12.5 International artificial intelligence applications and innovations, 5-7 June 2020, Halkidiki, Greece. IFIP advances in information and communication technology, 584. Cham: Springer [online], pages 358-369. Available from: https://doi.org/10.1007/978-3-030-49186-4_30

Early diagnosis of some life-threatening diseases such as cancers and heart is crucial for effective treatments. Supervised machine learning has proved to be a very useful tool to serve this purpose. Historical data of patients including clinical and... Read More about Overlap-based undersampling method for classification of imbalanced medical datasets..