Refining ladle slag entrapment prediction method and system adopting regression decision tree

The invention discloses a refining ladle slag entrapment prediction method and system adopting a regression decision tree. The method comprises the following steps: firstly, collecting refining data in the ladle bottom blowing refining process, then preprocessing the refining data, and inputting the preprocessed data into a machine learning regression decision tree model for training and prediction to obtain a prediction result. According to the method, a refining steel ladle structure is converted into a corresponding machine learning special structure, unnecessary interaction and coupling are avoided, network parameters with similar characteristics are reused, information of a steel ladle refining physical principle is introduced, dependence of a model on a sample is greatly reduced, and the method is suitable for large-scale popularization and application. And the modeling, training and learning efficiency and the model application success rate of the decision tree model can be remarkably improved. A decis