



@book {2301,
	title = {Chromatographic pattern recognition using optimized one-class classifiers},
	series = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)Lect. Notes Comput. Sci.},
	volume = {5524 LNCS},
	year = {2009},
	note = {Conference code: 77027Export Date: 21 November 2012Source: Scopusdoi: 10.1007/978-3-642-02172-5_58Language of Original Document: EnglishCorrespondence Address: Sousa, A. V.; Instituto de Engenharia Biom{\'e}dica, Rua Roberto Frias, Porto 4200-465, Portugal; email: ats@isep.ipp.ptReferences: Skurichina, M., Raudys, S., Duin, R.P.W., K-Nearest Neighbors Directed Noise Injection in Multilayer Perceptron Training (2000) IEEE Transactions on Neural Networks, 11;Chawla, N.V., Japkowicz, N., Kolcz, A., Editorial: Special Issue: Learning from Imbal-anced Data Sets (2004) Sigkdd Explorations, 6, pp. 1-6; 
Tax, D.M.J., (2001) One-class Classification; Concept-learning in the Absence of Counterexamples, , Ph.D. thesis: Delft University of Technology; 
Durand, G., Seta, N., Protein Glycosylation and Diseases: Blood and Urinary Oligosac-charides as Markers for Diagnosis and Therapeutic Monitoring (2000) Clin. Chem, 46, pp. 795-805; 
Sewell, A.C., Urinary Oligosaccharides. Techniques in Diagnostic Human (1991) Biochemical Genetics, pp. 219-231; 
Pekalska, E., Duin, R.P.W., Dissimilarity Representations Allow for Building Good Classifiers (2002) Pattern Recogn. Lett, 23, pp. 943-956; 
Sousa, A.V., Mendon{\c c}a, A.M., Campilho, A., Dissimilarity-based Classification of Chromatographic Profiles (2008) Pattern Analysis and Applications, 11 (3-4), pp. 409-423; 
Sousa, A.V., Mendon{\c c}a, A.M., Campilho, A., Minimizing the Imbalance Problem in Chromatographic Profile Classification with One-class Classifiers (2008) LNCS, 5112, pp. 413-422. , Campilho, A, Kamel, M.S, eds, ICIAR 2008, Springer, Heidelberg; 
Sousa, A.V., Mendon{\c c}a, A.M., Campilho, A., Chromatographic Pattern Classification (2008) IEEE Trans. on Biomedical Engineering, 55 (6), pp. 1687-1696; 
Visa, S., Ralescu, A., Learning Imbalanced and Overlapping Classes Using Fuzzy Sets (2003) Workshop on Learning from Imbalanced Datasets II, ICML, , Washington DC
Sponsors: International Association for Pattern Recognition (IAPR); Fundacao para a Ciencia e a Tecnologia (FCT)},
	month = {2009///},
	pages = {449 - 456},
	address = {Povoa de Varzim},
	abstract = {This paper presents a method for automating the selection of the rejection rate of one-class classifiers aiming at optimizing the classifier performance. These classifiers are used in a new classification approach to deal with class imbalance in Thin-Layer Chromatography (TLC) patterns, which is due to the huge difference between the number of normal and pathological cases, as a consequence of the rarity of Lysosomal Storage Disorders (LSD) diseases. The classification is performed in two decision stages, both implemented using optimized one-class classifiers: the first stage aims at recognizing most of the normal samples; the outliers of this first decision level are presented to the second stage, which is a multiclassifier prepared to deal with both pathological and normal patterns. The results that were obtained proved that the proposed methodology is able to overcome some of the difficulties associated with the choice of the rejection rate of one-class classifiers, and generally contribute to the minimization of the imbalance problem in TLC pattern classification. {\textcopyright} 2009 Springer Berlin Heidelberg.},
	keywords = {Chromatographic analysis, Class imbalance, Classification approach, Classifier performance, Classifiers, Decision levels, Image analysis, Imbalance problem, Learning systems, Lysosomal storage disorder, Multi-classifier, One-class classifier, Optimization, Pathological case, Pattern classification, Pattern recognition, Rejection rates, Thin layer chromatography},
	isbn = {03029743 (ISSN); 3642021719 (ISBN); 9783642021718 (ISBN)},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-68749107350\&partnerID=40\&md5=17cc4075de5306819dcd1bfc005171d6},
	author = {Sousa, A.V. and Mendon{\c c}a, A.M. and Campilho, A.}
}
