Model training method and device, electronic equipment and storage medium

The invention provides a model training method and device, electronic equipment and a storage medium, and belongs to the technical field of machine learning. The method comprises the steps of obtaining target data of at least two data sources corresponding to a target object and a target label of the target object; for each data source, inputting target data of the data source into a prediction model corresponding to the data source, so that the prediction model outputs prediction data corresponding to the data source to obtain at least two pieces of prediction data, wherein the prediction model is obtained by training sample data and sample labels of the data source in advance; and training a target model by using at least two pieces of prediction data and the target label until the target model converges. Therefore, the data volume for training the target model is reduced, and the training efficiency of the target model is improved. 本申请提供了一种模型训练方法、装置、电子设备及存储介质，属于机器学习技术领域。本申请通过获取目标对象对应的至少两个数据源的目标数据及所述目标对象的目标