Hyperparameter optimization is crucial for enhancing machine learning models. It involves selecting the right set of parameters to achieve the best performance. Optimizing hyperparameters can ...

Currently, the second most devastating form of cancer in people, particularly in women, is Breast Cancer (BC). In the healthcare industry, Machine Learning (ML) is commonly employed in fatal disease ...

Hyperparameter tuning is essential for achieving optimal performance in machine learning models. Bayesian Optimisation is effective for tuning complex models, particularly deep neural networks.

Abstract: Compared to the traditional machine learning models, deep neural networks (DNN) are known to be highly sensitive to the choice of hyperparameters. While the required time and effort for ...

Abstract: Hyperparameters play a crucial role in the model selection of machine learning algorithms. Tuning these hyperparameters can be exhaustive when the data is large. Bayesian optimisation has ...