التفاصيل البيبلوغرافية
| العنوان: |
Medical Diagnosis with a Novel SVM-CoDOA Based Hybrid Approach |
| المؤلفون: |
M. Hanefi Calp |
| المصدر: |
Brain: Broad Research in Artificial Intelligence and Neuroscience, Vol 9, Iss 4, Pp 6-16 (2018) |
| بيانات النشر: |
EduSoft publishing |
| سنة النشر: |
2018 |
| المجموعة: |
Directory of Open Access Journals: DOAJ Articles |
| مصطلحات موضوعية: |
support vector machines, cognitive development optimization algorithm, machine learning, artificial intelligence, medical diagnosis, Neurology. Diseases of the nervous system, RC346-429, Electronic computers. Computer science, QA75.5-76.95 |
| الوصف: |
Machine Learning is an important sub-field of the Artificial Intelligence and it has become a very critical task to train Machine Learning techniques via effective methods or techniques. Recently, researchers have tried to use alternative techniques to improve the ability of Machine Learning techniques. Moving from the explanations, the objective of this study is to introduce a novel SVM-CoDOA (Cognitive Development Optimization Algorithm trained Support Vector Machines) system for general medical diagnosis. In detail, the system consists of a SVM, which is trained by CoDOA, a newly developed optimization algorithm. As it is known, the use of optimization algorithms is an essential task in training and improving Machine Learning techniques. In this sense, the study has provided a medical diagnosis problem scope in order to show effectiveness of the SVM-CoDOA hybrid formation. |
| نوع الوثيقة: |
article in journal/newspaper |
| اللغة: |
English |
| تدمد: |
2067-3957 |
| Relation: |
https://www.edusoft.ro/brain/index.php/brain/article/view/859/1016; https://doaj.org/toc/2067-3957; https://doaj.org/article/3deed6b7744d4cf297ec5080592268fb |
| الاتاحة: |
https://doaj.org/article/3deed6b7744d4cf297ec5080592268fb |
| رقم الانضمام: |
edsbas.62D9E4DB |
| قاعدة البيانات: |
BASE |
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