Примеры использования Support vector на Английском языке и их переводы на Русский язык
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SVM- Support Vector Machine.
The results of applying the support vector machine method.
A support vector machine(with a Gaussian kernel) is a nonparametric large-margin classifier.
RBFs are also used as a kernel in support vector classification.
The support vector machine method(SVM- Support vector Machine) was first proposed by Vapnik V.N. 21, 22.
In their original paper,they use a support vector machine to get an error rate of 0.8.
The recognition algorithms have been built with the use of the statistical approach and support vector method.
It is suggested to use support vector machine and text's N-gramm features for solving the problem.
An example of an algorithm in this category is the Transductive Support Vector Machine TSVM.
In 2010, Qihoo 360 firstly launched QVM(Qihoo Support Vector Machine) to deal with the rapid increasing number of threats.
NMF is an instance of nonnegative quadratic programming(NQP),just like the support vector machine SVM.
The RVM has an identical functional form to the support vector machine, but provides probabilistic classification.
Key words: image processing and analysis, soft modeling,fractal dimension, support vector regression.
Support vector machines(SVMs) can effectively utilize a class of activation functions that includes both sigmoids and RBFs.
Research on machine learning theory,kernel methods for text analysis, support vector machines, kernel theory.
Support vector machine Sequential quadratic programming Linear programming Critical line method Nocedal, Jorge; Wright, Stephen J. 2006.
A central source of information on kernel based methods,including support vector machines, Gaussian processes.
Other models such as support vector machines are not, but methods exist to turn them into probabilistic classifiers.
Since then, these methods have been extended to other models such as support vector machines or logistic regression.
Research on kernel methods, support vector machines, neural networks, machine vision, bioinformatics, computational learning theory.
Specifically, we will write the parameters of our model in terms of only a subset of the training set called support vectors.
Key words: рattern recognition, gestures,machine learning, support vector machine, hidden Markov model, optimization.
Furthermore, there is often no need to compute φ{\displaystyle\varphi} directly during computation,as is the case with support vector machines.
Text Authorship Recognition Methods based on support vector machine// TUSURReports, No1(19), part 2, June 2009, pp.36-42.
The choice of loss function here gives rise to several well-known learning algorithms such as regularized least squares and support vector machines.
Investigated mathematic models(support vector machine and hidden Markov model) were adapted for applying in gesture recognition by devices with accelerometer.
In machine learning, kernel methods are a class of algorithms for pattern analysis,whose best known member is the support vector machine SVM.
Extensions of Existing Elements:Addition of multi-class classification for Support Vector Machines, improved representation for Association Rules, and the addition of Cox Regression Models.
For instance, they could be using an advanced data mining orpattern recognition systems such as neural networks or support vector machines.
Compared to that of support vector machines(SVM), the Bayesian formulation of the RVM avoids the set of free parameters of the SVM that usually require cross-validation-based post-optimizations.