Examples of 'support vector' in a sentence
Meaning of "support vector"
support vector - This phrase is used in machine learning and refers to a data point that is used to determine the classification or decision boundary of a machine learning model
How to use "support vector" in a sentence
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support vector
Neural nets and support vector machines.
The support vector machine under test.
We first consider the one of support vector machines.
Support vector machines often use the kernel trick.
Implement the support vector machine.
Support vector machines also typically work well for.
Speech emotion recognition using support vector machine.
Before the support vector machine can be.
One such approach is to use an ensemble of support vector machines.
We did this support vector machine analysis.
Applying a resampling filter to the samples of the resampling support vector.
The results of applying the support vector machine method.
Support vector machine.
Time series prediction using support vector machines.
Train a support vector machine based on the supplied training data.
See also
Resampling filter applied to the samples of the resampling support vector.
Geometric classifiers such as support vector machines are gradient models.
Support vector machines are algorithms that are based on statistical learning theory.
Classification using support vector machines and variables selection.
It worked only on raster images and did not support vector images.
Multiple support vector machines are trained to cover all possible combinations.
An example would be the tolerance hyperparameter for errors in support vector machines.
The classifier support vector machine is used in several problems in various areas of knowledge.
The function may be at least one portion of a kernel of a support vector machine.
Support vector machines are supervised learning models used for classification and regression analysis.
The first classifier and the second classifier may be support vector machines.
The use of support vector machines is a known technique for classification and separation of data.
A final alternative is to use kernelized models such as support vector regression with a polynomial kernel.
Support vector machines and the Bayes rule.
An algorithm for dimensionality reduction associated with a classification by support vector machines has been developed.
A support vector algorithm is a method for training an SVM.
RBFs are also used as a kernel in support vector classification.
Support Vector Machines are based on the concept of decision planes that define decision boundaries.
He has made particular contributions to support vector machines and kernel PCA.
It turns out that when we talk about an algorithm called the Support Vector.
Selected algorithms for the text classification were support vector machines and a naive Bayes classifier.
Support Vector Machines are particularly suited to handle such tasks.
Nonlinear modeling of a SOFC stack based on a least squares support vector machine.
Support Vector Machines is one of the most classical representant.
See the article on Support Vector Machines for more details.
Support Vector Machine as a classifier.
An example of an algorithm in this category is the Transductive Support Vector Machine TSVM.
Support vector machines, a technique from machine.
For example, a support vector machine is used.
So, that was a mathematical definition of what a support vector machine does.
Each support vector is a point in an n-dimensional space.
It turns out that, just like for support vector.
Finally, support vector machines are trained using the selected features.
One approach is to use a one-class support vector machine.
In support vector machines, it can reduce the time to find support vectors.
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