  Recently Liu et al. (Acta Mater., 2020) proposed a new divide-and-conquer
based machine learning method for predicting creep life of superalloys. The
idea is enlightening though, the prediction accuracy and intelligence remain to
be improved. In the present work, we modify the method by adding a
dimensionality reduction algorithm before the clustering step and introducing a
grid search algorithm to the regression model selection step. As a consequence,
the clustering result becomes much more desirable and the accuracy of predicted
creep life is dramatically improved. The root-mean-square error,
mean-absolute-percentage error and relevant coefficient of the original method
are 0.2341, 0.0595 and 0.9121, while those of the modified method are 0.0285,
0.0196, and 0.9806, respectively. Moreover, the ad-hoc determination of
hyperparameters in the original method is replaced by automated determination
of hyperparameters in the modified method, which considerably improves the
intelligence of the method.
