How Can Machine Learning Improve Predictive Accuracy?
Machine learning (ML) has emerged as a powerful tool to enhance predictive accuracy in catalysis. ML algorithms can analyze vast amounts of data to uncover hidden patterns and relationships that traditional methods might miss. For example:
Feature Engineering: Identifying key descriptors that influence catalytic performance. Model Training: Using training datasets to develop predictive models that can forecast catalyst behavior. Cross-validation: Ensuring model robustness by validating predictions against unseen data.
