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Support vector machine

时间:2016-12-14 21:23:40      阅读:323      评论:0      收藏:0      [点我收藏+]

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https://en.wikipedia.org/wiki/Support_vector_machine

In machine learning, support vector machines (SVMs, also support vector networks[1]) are supervised learning models with associated learning algorithms that analyze data used for classification and regression analysis. Given a set of training examples, each marked as belonging to one or the other of two categories, an SVM training algorithm builds a model that assigns new examples to one category or the other, making it a non-probabilistic binary linear classifier. An SVM model is a representation of the examples as points in space, mapped so that the examples of the separate categories are divided by a clear gap that is as wide as possible. New examples are then mapped into that same space and predicted to belong to a category based on which side of the gap they fall.

Support vector machine

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原文地址:http://www.cnblogs.com/yuanjiangw/p/6180611.html

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