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2  · A support vector machine (SVM) is a supervised learning algorithm used for many classification and regression problems, including signal processing medical applications, natural language processing, and speech and image recognition.. The objective of the SVM algorithm is to find a hyperplane that, to the best degree possible, separates data points …

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 · Support vector machines (SVMs) have recently found numerous applications in remote sensing. For this review we identified 108 relevant papers, with more than half published in the last 2.5 years ( Fig. 2 ). This increasing trend is expected to grow, making this a critical time for a review of existing work.

 · The relevance vector machine (RVM), a Bayesian extension of the support vector machine (SVM), has considerable potential for the analysis of remotely sensed data. Here, the RVM is introduced and ...

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 · To achieve fast image pre-scanning, a support vector machine (SVM) classifier was combined with a faster region-based convolutional neural network (faster R-CNN) object detector for the ...

（Support Vector Machine, SVM）（supervised learning）（generalized linear classifier）,（maximum-margin hyperplane）。SVM（hinge loss）（empirical risk） ...

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 · -Support Vector Machines using GMM Supervectors for Speaker Verification. Gaussian mixture models (GMMs) （text-independent） （speaker recognition）。. （GMMs） （target ...

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 · It is a sparse kernel decision machine that avoids computing posterior probabilities when building its learning model. SVM has been extensively used for classification, regression, novelty ...

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 · Background We apply a new machine learning method, the so-called Support Vector Machine method, to predict the protein structural class. Support Vector Machine method is performed based on the database derived from SCOP, in which protein domains are classified based on known structures and the evolutionary relationships and the …

 · On these datasets, survival support vector machines perform on par with the reference methods. Prediction performance for the five survival support vector models (vanbelle1, vanbelle2, SSVR ...

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 · Request PDF | On Feb 26, 2022, Tammineni Gnananandarao and others published Support Vector Machines-Based Prediction of Elastic Modulus for Granite …

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 · 163 . (, ) (binary/two-class classification)SVM。. SVM。. SVM,SVM。. SVM ...

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 · The foundations of Support Vector Machines (SVM) have been developed by Vapnik (1995) and are gaining popularity due to many attractive features, and promising empirical performance. The formulation embodies the Struc-tural Risk Minimisation (SRM) principle, which has been shown to be superior, (Gunn

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 · A supervised machine learning method, the support vector machine (SVM) algorithm [], has demonstrated high performance in solving classification problems in many biomedical fields, especially in bioinformatics [2, 3].In contrast to logistic regression, which depends on a pre-determined model to predict the occurrence or not of a binary event by …

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 ·  (3) Support vector machines.,Support Vector Machine,SV（SVM）。.,。. . ...