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About Lecture Notes - SVM
This document provides an overview of support vector machines (SVM). It discusses that SVMs can handle complex problems like image recognition through the use of kernels. It explains that SVMs are a class of linear models that use hyperplanes to classify data, but kernels allow them to handle nonlinear data. The document covers key SVM concepts like maximal margin classifiers, soft margin classifiers, slack variables, and kernels.
Detailed Information
Author: | ['Indrajit Mitali Paul'] |
---|---|
Publication Year: | 2020 |
Pages: | 13 |
Language: | English |
Format: | |
Price: | FREE |
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