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https://www.quora.com/What-is-the-difference-between-C-SVM-and-nu-SVM
Dec 18, 2016 · SVM use hyperplanes to perform classification. While performing classifications using SVM there are 2 types of SVM * C SVM * Nu SVM C and nu are regularisation parameters which help implement a penalty on the misclassifications that are performed ...
https://stats.stackexchange.com/questions/94118/difference-between-ep-svr-and-nu-svr-and-least-squares-svr
The difference between $\epsilon$-SVR and $\nu$-SVR is how the training problem is parametrized. Both use a type of hinge loss in the cost function. The $\nu$ parameter in $\nu$-SVM can be used to control the amount of support vectors in the resulting model. Given appropriate parameters, the exact same problem is solved. 1
https://www.csie.ntu.edu.tw/~cjlin/papers/nusvmtutorial.pdf
A Tutorial on ν-Support Vector Machines Pai-Hsuen Chen1, Chih-Jen Lin1, and Bernhard Scholkopf¨ 2? 1 Department of Computer Science and Information Engineering National Taiwan University Taipei 106, Taiwan 2 Max Planck Institute for Biological Cybernetics, Tubingen, Germany¨ [email protected] Abstract. We briefly describe the main ideas of statistical …Cited by: 339
https://scikit-learn.org/stable/modules/generated/sklearn.svm.NuSVC.html
Nu-Support Vector Classification. Similar to SVC but uses a parameter to control the number of support vectors. The implementation is based on libsvm. Read more in the User Guide. Parameters nu float, optional (default=0.5) An upper bound on the fraction of training errors and a lower bound of the fraction of support vectors.
https://en.wikipedia.org/wiki/Support_vector_machine
Support-vector machine weights have also been used to interpret SVM models in the past. Posthoc interpretation of support-vector machine models in order to identify features used by the model to make predictions is a relatively new area of research with special significance in the biological sciences. History
https://stackoverflow.com/questions/11230955/what-is-the-meaning-of-the-nu-parameter-in-scikit-learns-svm-class
The regularization in terms of nu is easier to interpret compared to C, but the nu SVM is usually harder to optimize and runtime doesn't scale as well as the C variant with number of input samples. More details (including formulas for A and B) can be found here: Chang CC, Lin CJ - "Training nu-support vector classifiers: theory and algorithms"
https://www.mathworks.com/help/stats/understanding-support-vector-machine-regression.html
Understanding Support Vector Machine Regression Mathematical Formulation of SVM Regression Overview. Support vector machine (SVM) analysis is a popular machine learning tool for classification and regression, first identified by Vladimir Vapnik and his colleagues in 1992.SVM regression is considered a nonparametric technique because it relies on kernel functions.
https://jakevdp.github.io/PythonDataScienceHandbook/05.07-support-vector-machines.html
Fitting a support vector machine¶ Let's see the result of an actual fit to this data: we will use Scikit-Learn's support vector classifier to train an SVM model on this data. For the time being, we will use a linear kernel and set the C parameter to a very large number (we'll discuss the meaning of …
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1780131/
2. nu-SVC: ν-Support Vector Classification (Binary Case) The parameter ν ∈ (0, 1) is an upper bound on the fraction of training errors and a lower bound of the fraction of support vectors .Cited by: 28
https://stats.stackexchange.com/questions/237382/difference-between-the-types-of-svm
I am new to support vector machines. Short explanation The svm function from the e1071 package in R offers various options: C-classification nu-classification one-classification (for novelty
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