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Support Vector Machine: Supervised Learning, Statistical Classification, Regression Analysis, Hyperplane, Generalization Error -

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2026-03-16
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Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. Support vector machines (SVMs) are a set of related supervised learning methods used for classification and regression. In simple words, given a set of training examples, each marked as belonging to one of two categories, an SVM training algorithm builds a model that predicts wheth ... Pilns apraksts

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Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. Support vector machines (SVMs) are a set of related supervised learning methods used for classification and regression. In simple words, given a set of training examples, each marked as belonging to one of two categories, an SVM training algorithm builds a model that predicts whether a new example falls into one category or the other. Intuitively, 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 on.

Vairāk informācijas

Izdevējs OmniScriptum
Izlaides gads 2026
Vāka tips Mīkstais vāks
EAN 9786130501990
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146,80 € 195,73 €