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The k-nearest neighbors classifier is a widely used classification method that has proven to be very effective in supervised learning tasks. In this paper, a fuzzy rough set method for prototype selection, focused on optimizing the behavior of this classifier, is presented. The hybridization with an evolutionary feature selection method is considered to further improve its performance, obtaining a...
The main objective of “time series analysis” is to discover the underlying structure of the time series, and thus, become able to forecast its “future values”. This process makes it possible to predict, control or simulate variables. Most of the time series modelling procedures try to forecast future values from lagged ones. Thus, the selection of the relevant lagged values to be used is a key step...
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