How Can Machine Learning Aid in Hyperparameter Tuning?
Machine learning (ML) can significantly aid in hyperparameter tuning by:
Predictive Modeling: ML models can predict the outcomes of catalytic reactions under different conditions. Optimization Algorithms: Algorithms such as genetic algorithms and Bayesian optimization can efficiently search the parameter space. Data Analysis: ML can handle large datasets to identify patterns and correlations. Automation: Automating the tuning process to reduce human intervention and error.
