Among these three regression models, random forest regression has the best prediction effect with a model score of 0.8564, which is the best prediction effect among the three models.

We developed a modeling approach for seasonal streamflow forecasts using a machine learning technique, random forest (RF), for runoff season flows (April 1–July 31 total) at the important gauge of ...

The study compares two models: random forest and support vector classifiers. The identification of potential natural gas price drivers that improve the model’s classification is crucial. The forecast ...