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Disambiguation of "Luengo, Julián"

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A study of statistical techniques and performance measures for genetics-based machine learning: accuracy and interpretability.

, , , and . Soft Comput., 13 (10): 959-977 (2009)

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Julian Scholl University of Stuttgart

Julian Schöpf University of Stuttgart

Julian Dinkelacker University of Stuttgart

Julian Fischer University of Stuttgart

Julian Beyer University of Stuttgart

 

Other publications of authors with the same name

KEEL Data-Mining Software Tool: Data Set Repository, Integration of Algorithms and Experimental Analysis Framework., , , , and . Multiple-Valued Logic and Soft Computing, 17 (2-3): 255-287 (2011)Domains of competence of fuzzy rule based classification systems with data complexity measures: A case of study using a fuzzy hybrid genetic based machine learning method., and . Fuzzy Sets and Systems, 161 (1): 3-19 (2010)On the use of Measures of Separability of Classes to Characterise the Domains of Competence of a Fuzzy Rule Based Classification System., and . IFSA/EUSFLAT Conf., page 1027-1032. (2009)Shared domains of competence of approximate learning models using measures of separability of classes., and . Inf. Sci., 185 (1): 43-65 (2012)Evaluating the classifier behavior with noisy data considering performance and robustness: The Equalized Loss of Accuracy measure., , and . Neurocomputing, (2016)On the characterization of noise filters for self-training semi-supervised in nearest neighbor classification., , , , and . Neurocomputing, (2014)A First Approach to Nearest Hyperrectangle Selection by Evolutionary Algorithms., , , and . ISDA, page 517-522. IEEE Computer Society, (2009)Tackling the problem of classification with noisy data using Multiple Classifier Systems: Analysis of the performance and robustness., , , and . Inf. Sci., (2013)A Study on the Noise Label Influence in Boosting Algorithms: AdaBoost, GBM and XGBoost., , and . HAIS, volume 10334 of Lecture Notes in Computer Science, page 268-280. Springer, (2017)Exact fuzzy k-nearest neighbor classification for big datasets., , , , and . FUZZ-IEEE, page 1-6. IEEE, (2017)