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EML: A Scalable, Transparent Meta-Learning Paradigm for Big Data Applications.

, , , and . Innovations in Big Data Mining and Embedded Knowledge, volume 159 of Intelligent Systems Reference Library, Springer, (2019)

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SAX-EFG: an evolutionary feature generation framework for time series classification., , and . GECCO, page 533-540. ACM, (2014)A new methodology for the GP theory toolbox., , and . GECCO, page 719-726. ACM, (2012)Quantifying Explainability in NLP and Analyzing Algorithms for Performance-Explainability Tradeoff., , , and . CoRR, (2021)Theoretical and Empirical Analysis of a Spatial EA Parallel Boosting Algorithm., , and . Evol. Comput., (2018)A Spatial EA Framework for Parallelizing Machine Learning Methods., , , and . PPSN (1), volume 7491 of Lecture Notes in Computer Science, page 206-215. Springer, (2012)Parallel boosted clustering., , , and . Neurocomputing, (2019)Theoretical and Empirical Analysis of a Parallel Boosting Algorithm., , and . CoRR, (2015)Feature and Kernel Evolution for Recognition of Hypersensitive Sites in DNA Sequences., , and . BIONETICS, volume 87 of Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, page 213-228. Springer, (2010)An analysis of a spatial EA parallel boosting algorithm., , and . GECCO, page 1053-1060. ACM, (2013)EML: A Scalable, Transparent Meta-Learning Paradigm for Big Data Applications., , , and . Innovations in Big Data Mining and Embedded Knowledge, volume 159 of Intelligent Systems Reference Library, Springer, (2019)