The experimenter environment of the NIP imperfection processor

Currently, most datasets from real-world problems contain low-quality data. In particular, within soft computing and data mining areas, the research and development of techniques that can deal with this type of data has been increased recently. In order to facilitate the design of experiments in thi...

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Bibliographic Details
Published in2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) pp. 2141 - 2148
Main Authors Martinez, Raquel, Cadenas, Jose M., Garrido, M. Carmen
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2014
Subjects
Data mining
Genetic algorithms
Low quality data
Noise
Robustness
Semantics
Softcomputing
Software tool
Software tools
Terminology
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Summary:Currently, most datasets from real-world problems contain low-quality data. In particular, within soft computing and data mining areas, the research and development of techniques that can deal with this type of data has been increased recently. In order to facilitate the design of experiments in this field and with these data, an experimenter environment in NIP imperfection processor software tool has been developed. This environment allows the generation of datasets with low-quality data, allowing the researcher to design experiments that analyze the robustness of different techniques which utilize this type of information in an easy and intuitive way.
ISSN:1098-7584
DOI:10.1109/FUZZ-IEEE.2014.6891654