نتایج جستجو برای: support vector machines

تعداد نتایج: 859628  

Journal: :Foundations of data science 2022

A support vector machine (SVM) is an algorithm that finds a hyperplane which optimally separates labeled data points in \begin{document}$ \mathbb{R}^n $\end{document} into positive and negative classes. The on the margin of this separating are called support vectors. We connect possible configurati...

2008
Kai Labusch Fabian Timm Thomas Martinetz

We introduce the OneClassMaxMinOver (OMMO) algorithm for the problem of one-class support vector classification. The algorithm is extremely simple and therefore a convenient choice for practitioners. We prove that in the hard-margin case the algorithm converges with O(1/ √ t) to the maximum margin solution of the support vector approach for one-class classification introduced by Schölkopf et al...

Ali Masoudi-Nejad, Hesam Torabi Dashti

Structural repetitive subsequences are most important portion of biological sequences, which play crucial roles on corresponding sequence’s fold and functionality. Biggest class of the repetitive subsequences is “Transposable Elements” which has its own sub-classes upon contexts’ structures. Many researches have been performed to criticality determine the structure and function of repetitiv...

رئیسی, احمد, زارع بند امیری, محمد, ستاره, سوگند, ظهیری اصفهانی, میثاق, عباسی, رضا,

Background and Objectives: Colon cancer is the third most common cancer in the world and the fourth most common cancer in Iran. It is very important to predict the cancer outcome and its basic clinical data. Due to to the high rate of colon cancer and the benefits of data mining to predict survival, the aim of this study was to survey two widely used machine learning algorithms, Bagging and Sup...

Journal: :Transactions of the Institute of Systems, Control and Information Engineers 2003

Journal: :Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 2014

Journal: :Social Science Research Network 2022

Classification models are very sensitive to data uncertainty, and finding robust classifiers that less uncertainty has raised great interest in the machine learning literature. This paper aims construct \emph{Support Vector Machine} under feature via two probabilistic arguments. The first classifier, \emph{Single Perturbation}, reduces local effect of with respect one given acts as a test could...

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