A Novel Hybrid Feature Importance and Feature Interaction Detection Framework for Predictive Optimization in Industry 4.0 Applications

arXiv:2403.02368v1 Announce Type: new
Abstract: Advanced machine learning algorithms are increasingly utilized to provide data-based prediction and decision-making support in Industry 4.0. However, the prediction accuracy achieved by the existing models is insufficient to warrant practical implementation in real-world applications. This is because not all features present in real-world datasets possess a direct relevance to the predictive analysis being conducted. Consequently, the careful incorporation of select features has the potential to yield a substantial positive impact on the outcome. To …

abstract accuracy advanced algorithms applications arxiv cs.ai cs.lg data decision detection feature framework hybrid implementation importance industry industry 4.0 machine machine learning machine learning algorithms making novel optimization practical prediction predictive support type world