Abstract
Two forms of the data-driven modelling are regression and classification. Based on some measured variables, both of them predict the value of one or more variables we are interested in. In case of regression there are continuous or ordered variables, in case of classification there are discrete or nominal variables needed to be predicted. Classification is also called supervised learning because the labels of the samples are known beforehand. This is the main difference between classification and clustering. The later is unsupervised learning since clusters want to be determined and the labels of the data points are not known.
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© 2007 Birkhäuser Verlag AG
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(2007). Fuzzy Model based Classifiers. In: Cluster Analysis for Data Mining and System Identification. Birkhäuser Basel. https://doi.org/10.1007/978-3-7643-7988-9_5
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DOI: https://doi.org/10.1007/978-3-7643-7988-9_5
Publisher Name: Birkhäuser Basel
Print ISBN: 978-3-7643-7987-2
Online ISBN: 978-3-7643-7988-9
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