Examples of using Support vector in English and their translations into Russian
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Research on kernel methods, support vector machines, neural networks,
pattern recognition systems such as neural networks or support vector machines.
Investigated mathematic models(support vector machine and hidden Markov model)
The choice of loss function here gives rise to several well-known learning algorithms such as regularized least squares and support vector machines.
whose best known member is the support vector machine SVM.
Addition of multi-class classification for Support Vector Machines, improved representation for Association Rules,
Recursive Feature Elimination algorithm, commonly used with Support Vector Machines to repeatedly construct a model and remove features with low weights.
One of the most commonly used algorithms is the transductive support vector machine, or TSVM which,
The underlying theory is close to the support vector machines(SVM) insofar as the GDA method provides a mapping of the input vectors into high-dimensional feature space.
Using string kernels with kernelized learning algorithms such as support vector machines allow such algorithms to work with strings, without having to translate these to fixed-length, real-valued feature vectors.
Statistical methods leverage elements from machine learning such as latent semantic analysis, support vector machines,"bag of words","Pointwise Mutual Information" for Semantic Orientation, and deep learning.
Support Vector Machines and memory-based learning have been shown to be the most successful approaches,
PMML allows for the representation of many other types of models including support vector machines, association rules,
They rose to great prominence with the popularity of the support vector machine(SVM) in the 1990s, when the SVM
Algorithms capable of operating with kernels include the kernel perceptron, support vector machines(SVM), Gaussian processes,
the"signed distance to the hyperplane" in a support vector machine.
Main techniques: Conditional random field Structured support vector machine Structured k-Nearest Neighbours Recurrent neural network,
such as a Gaussian mixture model[6], support vector model[22], and neural networks 23.
comparing the results obtained from the updated selection of classifiers based on the multilayer perceptron and the support vector machine 10.
Whereas support vector machines for supervised learning seek a decision boundary with maximal margin over the labeled data,