the performance comparison on the database of child autism disease by SVM Kernel types
محل انتشار: چهارمین کنفرانس بین المللی ریاضی و علوم کامپیوتر
سال انتشار: 1398
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 437
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شناسه ملی سند علمی:
ICNS04_047
تاریخ نمایه سازی: 8 تیر 1398
چکیده مقاله:
in this research, a database was used under the name Autistic Spectrum Disorder Screening Data for Children Data Set which was acquired from the data warehouse (UCI database repository). This dataset contains information for 292 children with 21 attributes. Using Weka tool. Mentioned data were classified by whether is diagnosed with autism disease or not. Using four types of support vector machine kernels. Normalized polynomial kernel, polynomial kernel, PUK kernel and RBF kernel classifiers utilized in data mining. The values which were used for performance comparisons are accuracy, precision, sensitivity, F measure and confusion matrix for each kernel. In this study, 100% successful results of accuracy have been obtained with each of polynomial kernel and PUK kernel
کلیدواژه ها:
Child autism disease ، weka ، performance comparisons ، support vector machine kernels ، confusion matrix ، normalized polynomial kernel ، polynomial kernel ، PUK kernel ، RBF kernel.
نویسندگان
Hardi S. Mohammed
Charmo University College Of Medicals and Applied SciencesApplied Computer Dep. Sulaimanyia- Iraq
Aso M. Aladdin
Charmo University College Of Medicals and Applied Sciences Applied Computer Dep Sulaimanyia- Iraq
Engin AVCI
Firat University Faculty of TechnologySoftware Engineering Department Elazig, Turkey