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Jan 30, 2014 � In this paper, we consider the related comparison problem, where the label indicates which element of the pair is better, or if there is no�...
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Support vector machines (SVMs, also support vector networks [1] ) are supervised max-margin models with associated learning algorithms that analyze data
The Support Vector Machine has proven to be a very effective tool for supervised classification. It was first introduced by Cortes and Vapnik (1995) as a way of�...
Support vector machines (SVM) were originally designed for binary classification. How to effectively extend it for multi-class classification is still an�...
Support Vector Machines (SVMs) have proved to be good alternative compared to other machine learning techniques specifically for classification problems.
Sep 4, 2020 � Comparison of support vector machine, na�ve bayes and logistic regression for assessing the necessity for coronary angiography.
The results indicate that solutions obtained by SVM training seem to be more robust with a smaller standard error compared to ANN training.
Support vector machines (SVMs) are a set of supervised learning methods used for classification, regression and outliers detection.
May 31, 2022 � The objective of this study is to compare different kernels of SVMs to classify prostate cancerous tissues.
Support vector machines (SVMs) were originally designed for binary classification. How to effectively extend it for multiclass classification is still an�...
