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• W2526975518 abstract "Wearable devices are currently used in researches related with the detection of human activities and the anamnesis of illnesses. Recent studies focused on the detection of simulated epileptic seizures have found that Fuzzy Rule Base Classifiers (FRBC) can be learnt with Ant Colony Systems (ACS) to efficiently deal with this problem. However, the computational requirements for obtaining these models is relatively high, which suggests that an alternative for reducing the learning cost would be rather interesting. Therefore, this study focuses on reducing the complexity of the model by using a discretization technique, more specifically, the discretization proposed in the SAX Time Series (TS) representation." @default.
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• W2526975518 date "2016-10-01" @default.
• W2526975518 modified "2023-09-23" @default.
• W2526975518 title "Learning Fuzzy Models with a SAX-based Partitioning for Simulated Seizure Recognition" @default.
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• W2526975518 doi "https://doi.org/10.1007/978-3-319-47364-2_3" @default.
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