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https://www.sciencedirect.com/science/article/pii/S0031320314005263
A support vector machine (SVM) is a popular algorithm for classification learning. The classical SVM effectively manages classification tasks defined by means of numerical attributes. However, both numerical and nominal attributes are used in practical tasks and the classical SVM does not fully consider the difference between them.Cited by: 15
https://www.researchgate.net/publication/2808303_An_Improved_Training_Algorithm_for_Support_Vector_Machines
We investigate the problem of training a Support Vector Machine (SVM) [1, 2, 7] on a very large date base (e.g. 50,000 data points) in the case in which the number of support vectors is also very ...
https://link.springer.com/article/10.1007%2Fs11425-013-4718-6
Dec 14, 2013 · Abstract We improve the twin support vector machine (TWSVM) to be a novel nonparallel hyperplanes classifier, termed as ITSVM (improved twin support vector machine), for binary classification.Cited by: 55
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1852326/
Here we describe a method that uses support vector machines together with a large set of informative features to improve contact map prediction. On the same data set, SVMcon outperforms the latest version of the CMAPpro contact map predictor [ 28, 35 ] and is ranked as one of the top predictors in the blind and independent CASP7 experiment.
https://ieeexplore.ieee.org/document/622408/
An improved training algorithm for support vector machines Abstract: We investigate the problem of training a support vector machine (SVM) on a very large database in the case in which the number of support vectors is also very large. Training a SVM is equivalent to solving a linearly constrained quadratic programming (QP) problem in a number ...
https://www.sciencedirect.com/science/article/pii/S0950705119303764
Support vector machine (SVM) was first proposed in Cortes and Vapnik, which has become a powerful tool in many fields such as classification, detection, pattern recognition, gene selection and etc. For more related works, the information can be found in Chen and …Author: Kai Qi, Hu Yang, Qingyu Hu, Dongjun Yang
https://www.researchgate.net/publication/283520159_Sensor_Multifault_Diagnosis_With_Improved_Support_Vector_Machines
In this paper, two multifault diagnosis methods based on improved support vector machine (SVM) are proposed for sensor fault detection and identification respectively. First, online sparse least...
https://www.youtube.com/watch?v=Y6RRHw9uN9o
Aug 15, 2017 · A Support Vector Machine (SVM) is a discriminative classifier formally defined by a separating hyperplane. In other words, given labeled training data (supervised learning), the algorithm outputs...Author: Augmented Startups
https://arxiv.org/abs/1801.00681
Jan 02, 2018 · Support vector machine is a new type of machine learning method proposed in 1990s. It can deal with classification and regression problems very successfully. Due to the excellent learning performance of support vector machine, the technology has become a hot research topic in the field of machine learning, and it has been successfully applied in many fields.Author: Shuheng Wang, Guohao Li, Yifan Bao
http://www.eurekaselect.com/84739/article
Title: Improved Prediction of Lysine Acetylation by Support Vector Machines VOLUME: 16 ISSUE: 8 Author(s):Songling Li, Hong Li, Mingfa Li, Yu Shyr, Lu Xie and Yixue Li Affiliation:Shanghai Center for Bioinformation Technology, 100 Qinzhou Road, Shanghai 200235, P.R. China. Keywords:Reversible lysine acetylation, support vector machine, protein coupling pattern
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