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Ensemble Merit Merge Feature Selection for Enhanced Multinomial Classification in Alzheimer’s Dementia
المؤلفون المشاركون
Sivapriya, T. R.
Kamal, A. R. Nadira Banu
Thangaiah, P. Ranjit Jeba
المصدر
Computational and Mathematical Methods in Medicine
العدد
المجلد 2015، العدد 2015 (31 ديسمبر/كانون الأول 2015)، ص ص. 1-11، 11ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2015-10-20
دولة النشر
مصر
عدد الصفحات
11
التخصصات الرئيسية
الملخص EN
The objective of this study is to develop an ensemble classifier with Merit Merge feature selection that will enhance efficiency of classification in a multivariate multiclass medical data for effective disease diagnostics.
The large volumes of features extracted from brain Magnetic Resonance Images and neuropsychological tests for diagnosis lead to more complexity in classification procedures.
A higher level of objectivity than what readers have is needed to produce reliable dementia diagnostic techniques.
Ensemble approach which is trained with features selected from multiple biomarkers facilitated accurate classification when compared with conventional classification techniques.
Ensemble approach for feature selection is experimented with classifiers like Naïve Bayes, Random forest, Support Vector Machine, and C4.5.
Feature search is done with Particle Swarm Optimisation to retrieve the subset of features for further selection with the ensemble classifier.
Features selected by the proposed C4.5 ensemble classifier with Particle Swarm Optimisation search, coupled with Merit Merge technique (CPEMM), outperformed bagging feature selection of SVM, NB, and Random forest classifiers.
The proposed CPEMM feature selection found the best subset of features that efficiently discriminated normal individuals and patients affected with Mild Cognitive Impairment and Alzheimer’s Dementia with 98.7% accuracy.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Sivapriya, T. R.& Kamal, A. R. Nadira Banu& Thangaiah, P. Ranjit Jeba. 2015. Ensemble Merit Merge Feature Selection for Enhanced Multinomial Classification in Alzheimer’s Dementia. Computational and Mathematical Methods in Medicine،Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1057968
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Sivapriya, T. R.…[et al.]. Ensemble Merit Merge Feature Selection for Enhanced Multinomial Classification in Alzheimer’s Dementia. Computational and Mathematical Methods in Medicine No. 2015 (2015), pp.1-11.
https://search.emarefa.net/detail/BIM-1057968
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Sivapriya, T. R.& Kamal, A. R. Nadira Banu& Thangaiah, P. Ranjit Jeba. Ensemble Merit Merge Feature Selection for Enhanced Multinomial Classification in Alzheimer’s Dementia. Computational and Mathematical Methods in Medicine. 2015. Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1057968
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1057968
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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