title: Learning ECOC Code Matrix for Multiclass Classification with Application to Glaucoma Diagnosis.
abstract: Classification of different mechanisms of angle closure glaucoma (ACG) is important for medical diagnosis. Error-correcting output code (ECOC) is an effective approach for multiclass classification. In this study, we propose a new ensemble learning method based on ECOC with application to classification of four ACG mechanisms. The dichotomizers in ECOC are first optimized individually to increase their accuracy and diversity (or interdependence) which is beneficial to the ECOC framework. Specifically, the best feature set is determined for each possible dichotomizer and a wrapper approach is applied to evaluate the classification accuracy of each dichotomizer on the training dataset using cross-validation. The separability of the ECOC codes is maximized by selecting a set of competitive dichotomizers according to a new criterion, in which a regularization term is introduced in consideration of the binary classification performance of each selected dichotomizer. The proposed method is experimentally applied for classifying four ACG mechanisms. The eye images of 152 glaucoma patients are collected by using anterior segment optical coherence tomography (AS-OCT) and then segmented, from which 84 features are extracted. The weighted average classification accuracy of the proposed method is 87.65 % based on the results of leave-one-out cross-validation (LOOCV), which is much better than that of the other existing ECOC methods. The proposed method achieves accurate classification of four ACG mechanisms which is promising to be applied in diagnosis of glaucoma.
authors.affiliation: State Key Laboratory of Fluid Power Transmission and Control, Zhejiang University, Hangzhou, 310027, People's Republic of China. bxl@zju.edu.cn.|School of Electrical and Electronics Engineering, Nanyang Technological University (NTU), Singapore, 639798, Singapore. bxl@zju.edu.cn.
authors.forename: Xiaolong
authors.initials: X
authors.lastname: Bai
authors.affiliation: School of Electrical and Electronics Engineering & School of Computer Engineering, Nanyang Technological University (NTU), Singapore, 639798, Singapore. issacniwas@ntu.edu.sg.
authors.forename: Swamidoss Issac
authors.initials: SI
authors.lastname: Niwas
authors.affiliation: School of Computer Engineering, Nanyang Technological University (NTU), Singapore, 639798, Singapore. wslin@ntu.edu.sg.
authors.forename: Weisi
authors.initials: W
authors.lastname: Lin
authors.affiliation: State Key Laboratory of Fluid Power Transmission and Control, Zhejiang University, Hangzhou, 310027, People's Republic of China. mbfju@zju.edu.cn.
authors.forename: Bing-Feng
authors.initials: BF
authors.lastname: Ju
authors.affiliation: School of Computer Engineering, Nanyang Technological University (NTU), Singapore, 639798, Singapore. asckkwoh@ntu.edu.sg.
authors.forename: Chee Keong
authors.initials: CK
authors.lastname: Kwoh
authors.affiliation: School of Electrical and Electronics Engineering, Nanyang Technological University (NTU), Singapore, 639798, Singapore. elpwang@ntu.edu.sg.
authors.forename: Lipo
authors.initials: L
authors.lastname: Wang
authors.affiliation: Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore (NUS), Singapore, 119228, Singapore. chelvin@gmail.com.
authors.forename: Chelvin C
authors.initials: CC
authors.lastname: Sng
authors.affiliation: Eye Surgery Centre, National University Health System (NUHS), Singapore, 119228, Singapore. mcdaquino@gmail.com.
authors.forename: Maria C
authors.initials: MC
authors.lastname: Aquino
authors.affiliation: Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore (NUS), Singapore, 119228, Singapore. ophchewp@nus.edu.sg.
authors.forename: Paul T K
authors.initials: PT
authors.lastname: Chew
mesh_terms: D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D015812:Glaucoma, Angle-Closure / Q000175:diagnosis*; D006801:Humans; D000069550:Machine Learning; D012680:Sensitivity and Specificity; D041623:Tomography, Optical Coherence
keywords: Dichotomizers; Ensemble learning; Error-correcting-output-coding (ECOC); Feature selection; Glaucoma; Multiclass classification