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In this study we estimate the stellar ages of LAMOST DR5 Red Giant Branch(RGB) stars based on the Gradient Boosting Decision Tree algorithm (GBDT). Weused 2088 RGB stars extracted from the APOKASC-2 astero-seismological catalogas training data-set. After selecting the parameters highly correlated with ageusing GBDT, we apply the same GBDT method to the new catalog of more than690,000 stars classified as RGB stars. The test data-set shows that the medianrelative error is around 0.3 $\%$ for the method. We also compare the predictedages of RGB stars with other studies (e.g. based on APOGEE), and find that theyare almost consistent. The final uncertainty is about 14 $\%$ compared to openclusters' ages. Then we present the spatial distribution of the RGB samplehaving an age determination and discuss some systematics. All these diagnosticsshow that one can apply the GBDT method to other stellar samples to estimateatmospheric parameters and age.

Age Determination of LAMOST Red Giant Branch stars based on the Gradient Boosting Decision Tree method