| Title | The class imbalance problem in TLC image classification |
| Publication Type | Book |
| Year of Publication | 2006 |
| Authors | Sousa, AV, Mendonça, AM, Campilho, A |
| Series Title | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)Lect. Notes Comput. Sci. |
| Volume | 4142 LNCS |
| Number of Pages | 513 - 523 |
| City | Povoa de Varzim |
| ISBN Number | 03029743 (ISSN); 3540448942 (ISBN); 9783540448945 (ISBN) |
| Keywords | Chromatographic analysis, Class imbalanced problem, Classification (of information), Hierarchical systems, Lysosomal Storage Disorders (LSD), Medical imaging, Multiclassifier system, Problem solving, Thin-Layer Chromatography (TLC) images |
| Abstract | The paper presents the methodology developed to solve the class imbalanced problem that occurs in the classification of Thin-Layer Chromatography (TLC) images. The proposed methodology is based on resampling, and consists in the undersampling of the majority class (normal class), while the minority classes, which contain Lysosomal Storage Disorders (LSD) samples, are oversampled with the generation of synthetic samples. For image classification two approaches are presented, one based on a hierarchical classifier and another uses a multiclassifier system, where both classifiers are trained and tested using balanced data sets. The results demonstrate a better performance of the multiclassifier system using the balanced sets. © Springer-Verlag Berlin Heidelberg 2006. |
| URL | http://www.scopus.com/inward/record.url?eid=2-s2.0-33749667604&partnerID=40&md5=3b4a717035de29f4bed59a04613836cd |
