In:
Synlett, Georg Thieme Verlag KG, Vol. 32, No. 18 ( 2021-11), p. 1843-1848
Abstract:
The prediction of the initial reaction rate in the tungsten-catalyzed epoxidation of alkenes by using a machine learning approach is demonstrated. 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.
Type of Medium:
Online Resource
ISSN:
0936-5214
,
1437-2096
Language:
English
Publisher:
Georg Thieme Verlag KG
Publication Date:
2021
detail.hit.zdb_id:
2042012-2
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