Support vector machines: Revision history

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9 July 2024

  • curprev 10:5510:55, 9 July 2024‎ Ai talk contribs‎ 7,084 bytes +7,084‎ Created page with "== Introduction == Support vector machines (SVMs) are a set of supervised learning methods used for classification, regression, and outlier detection. Developed by Vladimir Vapnik and his colleagues in the 1990s, SVMs are grounded in the principles of statistical learning theory. They are particularly effective in high-dimensional spaces and are versatile in both linear and non-linear classifications. == Theory and Principles == === Linear SVM === A linear SVM aims to f..."
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