SDRDPy: An application to graphically visualize the knowledge obtained with supervised descriptive rule algorithms

SDRDPy is a desktop application that allows experts an intuitive graphic and tabular representation of the knowledge extracted by any supervised descriptive rule discovery algorithm. The application is able to provide an analysis of the data showing the relevant information of the data set and the relationship between the rules, data and the quality measures associated for each rule regardless of the tool where algorithm has been executed. All of the information is presented in a user-friendly application in order to facilitate expert analysis and also the exportation of reports in different formats.

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Publication Details

Journal
SoftwareX
Published
2024-11-04
DOI
https://doi.org/10.1016/j.softx.2024.101939
Primary Topic
Data Mining Algorithms and Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

SDRDPy: An application to graphically visualize the knowledge obtained with supervised descriptive rule algorithms

Pedro González, C. J. Carmona, María Asunción Padilla-Rascón
SoftwareX
Data Mining Algorithms and Applications
article

SDRDPy: An application to graphically visualize the knowledge obtained with supervised descriptive rule algorithms

Pedro González, C. J. Carmona, María Asunción Padilla-Rascón
article en

Abstract

SDRDPy is a desktop application that allows experts an intuitive graphic and tabular representation of the knowledge extracted by any supervised descriptive rule discovery algorithm. The application is able to provide an analysis of the data showing the relevant information of the data set and the relationship between the rules, data and the quality measures associated for each rule regardless of the tool where algorithm has been executed. All of the information is presented in a user-friendly application in order to facilitate expert analysis and also the exportation of reports in different formats.

SoftwareXVol. 28
Universidad de Jaén (ES)
Ministerio de Ciencia, Innovación y Universidades, Ministerio de Ciencia e Innovación, Universidad de Jaén
Openalex Percentile: Top 70%
Data Mining Algorithms and Applications
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