Product Attribute Forecast: Adaptive Model Selection Using Real-Time Machine Learning
Product Attribute Forecast: Adaptive Model Selection Using Real-Time Machine Learning is a scholarly work, published in 2018 in ''IFAC Proceedings Volumes''. The main subjects of the publication include selection (genetic algorithm), model selection, product, data mining, artificial intelligence, protein expression (biotechnology), scale, process, model predictive control, chemometrics, machine learning, feature selection, and computer science. In real-time, the framework evaluates several machine learning algorithms and chooses the most representative algorithm based on current dynamics of the system.