| Autor: |
Cateni, Silvia, Ritacco, Antonio, Iannino, Vincenzo, Colla, Valentina, Vannucci, Marco, Dettori, Stefano |
| Předmět: |
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| Zdroj: |
International Journal of Simulation: Systems, Science & Technology; Oct2018, Vol. 19 Issue 5, p24.1-24.7, 7p |
| Abstrakt: |
The paper presents a tool supporting the smart pre-elaboration and analysis of large datasets that implements complex algorithms for variable selection and outliers detection. These pre-elaboration stages are fundamental for further data exploitation in modelling and classification tasks. Moreover, the identification of anomalous data and of the most relevant variables affecting a process or a phenomenon is crucial in data mining, as it supports the extraction of knowledge from the data. The proposed algorithms come equipped with a user-friendly graphical interface that helps the interpretation of the analysis and can be applied to any context, especially in industrial ones. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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