首页>
外国专利>
INTEGRATING MACHINE-LEARNING MODELS IMPACTING DIFFERENT FACTOR GROUPS FOR DYNAMIC RECOMMENDATIONS TO OPTIMIZE A PARAMETER
INTEGRATING MACHINE-LEARNING MODELS IMPACTING DIFFERENT FACTOR GROUPS FOR DYNAMIC RECOMMENDATIONS TO OPTIMIZE A PARAMETER
展开▼
机译：集成了影响不同因子组的机器学习模型，以便动态建议优化参数
展开▼
页面导航
摘要
著录项
相似文献
摘要
A method for integrating a machine learning (ML) model that impacts different factor groups for generating a dynamic recommendation to collectively optimize a parameter is provided. The method includes (i) processing a specification information and operational data associated with a demand management service obtained from client devices (116A-N), (ii) training the ML models with processed specification information and the operational data to obtain a trained ML model that includes an anticipation ML model that optimizes demand parameter or recommendation ML model that generates recommendation for optimizing a factor group, (iii) integrating the trained ML model with the ML models by setting an output of a first ML model as a feature of a second ML model and (iv) determining a demand of a product using the trained ML models and quantifying probabilistic values that signify prediction of the demand.
展开▼
