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Improvement of subgroup descriptions in noisy data by detecting exceptions.

, , , and . Prog. Artif. Intell., 7 (1): 55-64 (2018)

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A distributed evolutionary fuzzy system-based method for the fusion of descriptive emerging patterns in data streams., , , and . Inf. Fusion, (2023)Subgroup Discovery on Multiple Instance Data., , , , and . Int. J. Comput. Intell. Syst., 12 (2): 1602-1612 (2019)TSFEDL: A python library for time series spatio-temporal feature extraction and prediction using deep learning., , , , , , and . Neurocomputing, (2023)Improvement of subgroup descriptions in noisy data by detecting exceptions., , , and . Prog. Artif. Intell., 7 (1): 55-64 (2018)A Preliminary Analysis on Software Frameworks for the Development of Spiking Neural Networks., and . HAIS, volume 12886 of Lecture Notes in Computer Science, page 564-575. Springer, (2021)A Preliminary Many Objective Approach for Extracting Fuzzy Emerging Patterns., , , and . SOCO, volume 1268 of Advances in Intelligent Systems and Computing, page 100-110. Springer, (2020)A first approach to handle fuzzy emerging patterns mining on big data problems: The EvAEFP-spark algorithm., , , and . FUZZ-IEEE, page 1-6. IEEE, (2017)An overview of emerging pattern mining in supervised descriptive rule discovery: taxonomy, empirical study, trends, and prospects., , , , and . WIREs Data Mining Knowl. Discov., (2018)E2PAMEA: A fast evolutionary algorithm for extracting fuzzy emerging patterns in big data environments., , , , and . Neurocomputing, (2020)FEPDS: A Proposal for the Extraction of Fuzzy Emerging Patterns in Data Streams., , , , and . IEEE Trans. Fuzzy Syst., 28 (12): 3193-3203 (2020)