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A fuzzy adaptive evolutionary-based feature selection and machine learning framework for single and multi-objective body fat prediction
A fuzzy set theory determines appropriate levels of exploration and exploitation while managing parameterisation and computational costs.
Uncertainty-Aware Performance Prediction for Highly Configurable Software Systems via Bayesian Neural Networks
We also develop a novel uncertainty calibration technique to ensure the reliability of the confidence intervals generated by a Bayesian prediction model.
Explainable and Optimally Configured Artificial Neural Networks for Attack Detection in Smart Homes
Also, selection of right hyperparameters for ANN architecture plays a crucial role in the accurate detection of security attacks, especially when it come to identifying the subcategories of attacks.
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