MRI brain tumor classification using Support Vector Machines and meta-heuristic method

2015 ◽  
Author(s):  
Ahmed Kharrat ◽  
Mohamed Ben Halima ◽  
Mounir Ben Ayed
Keyword(s):  
Brain Tumor ◽  
Support Vector Machines ◽  
Heuristic Method ◽  
Tumor Classification ◽  
Support Vector ◽  
Mri Brain ◽  
Vector Machines

scholarly journals Asymptotic Behaviors of Support Vector Machines with Gaussian Kernel

2003 ◽  
Vol 15 (7) ◽  
pp. 1667-1689 ◽  
Author(s):  
S. Sathiya Keerthi ◽  
Chih-Jen Lin
Keyword(s):  
Support Vector Machines ◽  
Model Selection ◽  
Heuristic Method ◽  
Gaussian Kernel ◽  
Support Vector ◽  
Svm Classifier ◽  
Vector Machines ◽  
Rbf Kernel ◽  
Linear Svm ◽  
Generalization Errors

Support vector machines (SVMs) with the gaussian (RBF) kernel have been popular for practical use. Model selection in this class of SVMs involves two hyper parameters: the penalty parameter C and the kernel width σ. This letter analyzes the behavior of the SVM classifier when these hyper parameters take very small or very large values. Our results help in understanding the hyperparameter space that leads to an efficient heuristic method of searching for hyperparameter values with small generalization errors. The analysis also indicates that if complete model selection using the gaussian kernel has been conducted, there is no need to consider linear SVM.

scholarly journals Breast tumor classification in ultrasound images using support vector machines and neural networks

2016 ◽  
Vol 32 (3) ◽  
pp. 283-292 ◽  
Author(s):  
Carmina Dessana Lima Nascimento ◽  
Sérgio Deodoro de Souza Silva ◽  
Thales Araújo da Silva ◽  
Wagner Coelho de Albuquerque Pereira ◽  
Marly Guimarães Fernandes Costa ◽  
...  
Keyword(s):  
Neural Networks ◽  
Support Vector Machines ◽  
Breast Tumor ◽  
Tumor Classification ◽  
Support Vector ◽  
Ultrasound Images ◽  
Vector Machines ◽  
Breast Tumor Classification
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