New Methods for Feature Ranking

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F10%3A00166078" target="_blank" >RIV/68407700:21230/10:00166078 - isvavai.cz</a>
Alternative codes found
RIV/68407700:21240/10:00166078
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
New Methods for Feature Ranking
Original language description
Most of Feature Ranking and Feature Selection approaches can be used for categorial data only. Some of them rely on statistical measures of the data, some are tailored to a specific data mining algorithm (wrapper approach). In this paper we present new methods for feature ranking and selection obtained as a combination of the above mentioned approaches. The data mining algorithm (GAME) is designed for numerical data, but it can be applied to categorial data as well. It incorporates feature selection mechanisms and new methods, proposed in this paper, derive feature ranking from final data mining model. The rank of each feature selected by model is computed by processing correlations of outputs between neighboring model?s neurons in different ways. We used four different methods based on fuzzy logic, certainty factors and simple calculus. The performance of these four feature ranking methods was tested on artificial data sets, on well known Ionosphere data set and on well known Housing
Czech name
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Czech description
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Project
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Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)<br>V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Publication year
2010
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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