Book ; Online: Ensemble-based Hybrid Optimization of Bayesian Neural Networks and Traditional Machine Learning Algorithms
2023
Abstract: This research introduces a novel methodology for optimizing Bayesian Neural Networks (BNNs) by synergistically integrating them with traditional machine learning algorithms such as Random Forests (RF), Gradient Boosting (GB), and Support Vector Machines ( ...
| Abstract | This research introduces a novel methodology for optimizing Bayesian Neural Networks (BNNs) by synergistically integrating them with traditional machine learning algorithms such as Random Forests (RF), Gradient Boosting (GB), and Support Vector Machines (SVM). Feature integration solidifies these results by emphasizing the second-order conditions for optimality, including stationarity and positive definiteness of the Hessian matrix. Conversely, hyperparameter tuning indicates a subdued impact in improving Expected Improvement (EI), represented by EI(x). Overall, the ensemble method stands out as a robust, algorithmically optimized approach. |
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| Keywords | Computer Science - Machine Learning ; Computer Science - Artificial Intelligence |
| Publishing date | 2023-10-09 |
| Publishing country | us |
| Document type | Book ; Online |
| Database | BASE - Bielefeld Academic Search Engine (life sciences selection) |
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