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https://en.wikipedia.org/wiki/Least-squares_support-vector_machine
From support-vector machine to least-squares support-vector machine. Given a training set {,} = with input data ∈ and corresponding binary class labels ∈ {−, +}, the SVM classifier, according to Vapnik’s original formulation, satisfies the following conditions:
https://brilliant.org/wiki/support-vector-machines/
The original support vector machines (SVMs) were invented by Vladimir Vapnik in 1963.They were designed to address a longstanding problem with logistic regression, another machine learning technique used to classify data.. Logistic regression is a probabilistic binary linear classifier, meaning it calculates the probability that a data point belongs to one of two classes.
https://www.quora.com/What-is-a-Support-Vector-Machine
Jan 15, 2016 · Support Vector Machine (SVM) is a supervised binary classification algorithm. Given a set of points of two types in [math]N[/math] dimensional place SVM generates a [math](N-1)[/math] dimensional hyperplane to separate those points into two groups...
http://support-vector-machines.org/
Kernel-based techniques (such as support vector machines, Bayes point machines, kernel principal component analysis, and Gaussian processes) represent a major development in machine learning algorithms. Support vector machines (SVM) are a group of supervised learning methods that can be applied to classification or regression.
https://ko.wikipedia.org/wiki/%EC%84%9C%ED%8F%AC%ED%8A%B8_%EB%B2%A1%ED%84%B0_%EB%A8%B8%EC%8B%A0
서포트 벡터 머신(support vector machine, SVM.)은 기계 학습의 분야 중 하나로 패턴 인식, 자료 분석을 위한 지도 학습 모델이며, 주로 분류와 회귀 분석을 위해 사용한다. 두 카테고리 중 어느 하나에 속한 데이터의 집합이 주어졌을 때, SVM 알고리즘은 주어진 데이터 집합을 바탕으로 하여 새로운 데이터가 ...
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