Abstract
We saw in the previous chapter that in classification or regression tasks, patterns are represented by feature vectors in an R d feature space. In the particular case of a classifier, the main goal is to divide the feature space into regions assigned to the classification classes. These regions are called decision regions. If a feature vector falls into a certain decision region the associated pattern is assigned to the corresponding class.
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© 2001 Springer-Verlag Berlin Heidelberg
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Marques de Sá, J.P. (2001). Pattern Discrimination. In: Pattern Recognition. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-56651-6_2
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DOI: https://doi.org/10.1007/978-3-642-56651-6_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-62677-7
Online ISBN: 978-3-642-56651-6
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