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A Novel Weighted Support Vector Machine Based on Particle Swarm Optimization for Gene Selection and Tumor Classification
المؤلفون المشاركون
Abdi, Mohammad Javad
Hosseini, Seyed Mohammad
Rezghi, Mansoor
المصدر
Computational and Mathematical Methods in Medicine
العدد
المجلد 2012، العدد 2012 (31 ديسمبر/كانون الأول 2012)، ص ص. 1-7، 7ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2012-07-26
دولة النشر
مصر
عدد الصفحات
7
التخصصات الرئيسية
الملخص EN
We develop a detection model based on support vector machines (SVMs) and particle swarm optimization (PSO) for gene selection and tumor classification problems.
The proposed model consists of two stages: first, the well-known minimum redundancy-maximum relevance (mRMR) method is applied to preselect genes that have the highest relevance with the target class and are maximally dissimilar to each other.
Then, PSO is proposed to form a novel weighted SVM (WSVM) to classify samples.
In this WSVM, PSO not only discards redundant genes, but also especially takes into account the degree of importance of each gene and assigns diverse weights to the different genes.
We also use PSO to find appropriate kernel parameters since the choice of gene weights influences the optimal kernel parameters and vice versa.
Experimental results show that the proposed mRMR-PSO-WSVM model achieves highest classification accuracy on two popular leukemia and colon gene expression datasets obtained from DNA microarrays.
Therefore, we can conclude that our proposed method is very promising compared to the previously reported results.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Abdi, Mohammad Javad& Hosseini, Seyed Mohammad& Rezghi, Mansoor. 2012. A Novel Weighted Support Vector Machine Based on Particle Swarm Optimization for Gene Selection and Tumor Classification. Computational and Mathematical Methods in Medicine،Vol. 2012, no. 2012, pp.1-7.
https://search.emarefa.net/detail/BIM-463288
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Abdi, Mohammad Javad…[et al.]. A Novel Weighted Support Vector Machine Based on Particle Swarm Optimization for Gene Selection and Tumor Classification. Computational and Mathematical Methods in Medicine No. 2012 (2012), pp.1-7.
https://search.emarefa.net/detail/BIM-463288
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Abdi, Mohammad Javad& Hosseini, Seyed Mohammad& Rezghi, Mansoor. A Novel Weighted Support Vector Machine Based on Particle Swarm Optimization for Gene Selection and Tumor Classification. Computational and Mathematical Methods in Medicine. 2012. Vol. 2012, no. 2012, pp.1-7.
https://search.emarefa.net/detail/BIM-463288
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-463288
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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