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BBA-LAHC is a novel nature-inspired feature selection algorithm developed by hybridizing Binary Bat Algorithm (BBA) and Late Acceptance Hill-Climbing (LAHC) to select the optimal subset from the said feature vectors in order to reduce the model complexity.

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BBA-LAHC

BBA-LAHC is a novel nature-inspired feature selection algorithm developed by hybridizing Binary Bat Algorithm (BBA) and Late Acceptance Hill-Climbing (LAHC) to select the optimal subset from the said feature vectors in order to reduce the model complexity.

The research paper can be found in: https://ieeexplore.ieee.org/document/9210572

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BBA-LAHC is a novel nature-inspired feature selection algorithm developed by hybridizing Binary Bat Algorithm (BBA) and Late Acceptance Hill-Climbing (LAHC) to select the optimal subset from the said feature vectors in order to reduce the model complexity.

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