<jats:p>The prediction of the initial reaction rate in the tungsten-catalyzed epoxidation of alkenes is demonstrated using a machine learning approach. The ensemble learning framework used in this study consists of random sampling with replacement from the training dataset, the construction of several predictive models (weak learners), and the combination of their outputs. This approach enables us to obtain a reasonable prediction model that avoids the problem of overfitting, even when analyzing a small dataset.</jats:p>
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