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Support Vector Machine

The Support Vector Machine, introduced by Corinna Cortes and Vladimir Vapnik in 1995, is a classifier that finds the optimal separating hyperplane between classes in a high-dimensional space. It chooses the boundary that leaves the widest possible margin to the nearest training points, which makes its decisions robust on new data.

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Support Vector Machine (SVM — Classification)

Taksonomisk metoderegister · ml-model / machine-learning

Cortes, C. & Vapnik, V. (1995). Support-Vector Networks. Machine Learning, 20, 273–297. · DOI 10.1007/BF00994018

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Same method familyK-Nearest Neighborsmachine-suggested · Relational suggestion, not evidence.See alsoLogistic Regressionmachine-suggested · Relational suggestion, not evidence.Same method familyNaive Bayesmachine-suggested · Relational suggestion, not evidence.Same method familyRandom Forestmachine-suggested · Relational suggestion, not evidence.Same method familySupport Vector Regressionmachine-suggested · Relational suggestion, not evidence.