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https://metacpan.org/pod/Algorithm::SVM
Jan 22, 2008 · Algorithm::SVM implements a Support Vector Machine for Perl. Support Vector Machines provide a method for creating classifcation functions from a set of labeled training data, from which predictions can be made for subsequent …
https://metacpan.org/pod/Algorithm::SVMLight
Nov 25, 2008 · This module implements a perl interface to Thorsten Joachims' SVMLight package: SVMLight is an implementation of Vapnik's Support Vector Machine [Vapnik, 1995] for the problem of pattern recognition, for the problem of regression, and for the problem of learning a ranking function.
https://www.csie.ntu.edu.tw/~cjlin/libsvm/
A practical guide to support vector classification An introductory video for windows users. Other implementation documents: R.-E. Fan, P.-H. Chen, and C.-J. Lin. Working set selection using the second order information for training SVM. Journal of Machine Learning Research 6, 1889-1918, 2005. You can also find a pseudo code there.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2099486/
Nov 01, 2007 · Support Vector Machine. Support Vector Machines (SVMs) provide a very efficient mechanism to construct a separating hyperplane (see Fig. Fig.1), 1), surrounded by the thickest margin, using a set of training data. Prediction is made according to some measure of the distance between the test data and the hyperplane.
https://www.geeksforgeeks.org/classifying-data-using-support-vector-machinessvms-in-python/
Apr 30, 2017 · In machine learning, support vector machines (SVMs, also support vector networks) are supervised learning models with associated learning algorithms that analyze data used for classification and regression analysis. A Support Vector Machine (SVM) is a discriminative classifier formally defined by a separating hyperplane.2/5
https://www.sciencedirect.com/topics/neuroscience/support-vector-machine
The support vector machine is classified on the basis of number of classes used for the training structure of that class. The following are the extension of SVM. • Multiclass SVM. Multiclass SVM aims to assign labels to instances by using support vector machines, where the labels are drawn from a finite set of several elements.
https://www.r-bloggers.com/machine-learning-using-support-vector-machines/
Apr 19, 2017 · Support Vector Machines (SVM) is a data classification method that separates data using hyperplanes. The concept of SVM is very intuitive and easily understandable. If we have labeled data, SVM can be used to generate multiple separating hyperplanes such that the data space is divided into segments and each segment contains only one kind of … Continue …
https://www.svm-tutorial.com/2014/11/svm-understanding-math-part-1/
Nov 02, 2014 · What is the goal of the Support Vector Machine (SVM)? The goal of a support vector machine is to find the optimal separating hyperplane which maximizes the margin of the training data. The first thing we can see from this definition, is that a SVM needs training data. Which means it is a supervised learning algorithm.
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