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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 data.
https://www.geeksforgeeks.org/classifying-data-using-support-vector-machinessvms-in-r/
Classifying data using Support Vector Machines(SVMs) in R In machine learning, Support vector machine(SVM) are supervised learning models with associated learning algorithms that analyze data used for classification and regression analysis. It is mostly used in classification problems.
https://www.edureka.co/blog/support-vector-machine-in-r/
SVM (Support Vector Machine) is a supervised machine learning algorithm which is mainly used to classify data into different classes. Unlike most algorithms, SVM makes use of a hyperplane which acts like a decision boundary between the various classes.Author: Zulaikha Lateef
https://www.rdocumentation.org/packages/e1071/versions/1.7-3/topics/svm
svm is used to train a support vector machine. It can be used to carry out general regression and classification (of nu and epsilon-type), as well as density-estimation. It can be used to carry out general regression and classification (of nu and epsilon-type), as well as density-estimation.
https://www.listendata.com/2017/01/support-vector-machine-in-r-tutorial.html
Support Vector Machine Simplified using R This tutorial describes theory and practical application of Support Vector Machines (SVM) with R code. It's a popular supervised learning algorithm (i.e. classify or predict target variable). It works both for classification and regression problems.
https://dataaspirant.com/2017/01/19/support-vector-machine-classifier-implementation-r-caret-package/
Jan 19, 2017 · The principle behind an SVM classifier (Support Vector Machine) algorithm is to build a hyperplane separating data for different classes. This hyperplane building procedure varies and is the main task of an SVM classifier.
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