- 专利标题: SYSTEM AND METHOD FOR FIELD VALUE RECOMMENDATIONS BASED ON CONFIDENCE LEVELS IN ANALYZED DATASET
-
申请号: US17247764申请日: 2020-12-22
-
公开(公告)号: US20210182716A1公开(公告)日: 2021-06-17
- 发明人: Kristen Noriko Muramoto , Son Thanh Chang , Clement Jacques Antoine Tussoit , Melissa Hoang , Chaitanya Malla , Orjan N. Kjellberg , Carlos Enrique Mogollan Jimenez , George Hu
- 申请人: salesforce.com, inc.
- 申请人地址: US CA San Francisco
- 专利权人: salesforce.com, inc.
- 当前专利权人: salesforce.com, inc.
- 当前专利权人地址: US CA San Francisco
- 主分类号: G06N5/04
- IPC分类号: G06N5/04 ; G06F9/451 ; G06N99/00 ; G06F3/0484 ; G06F3/0482
摘要:
A method of training a predictive model to predict a likely field value for one or more user selected fields within an application. The method comprises providing a user interface for user selection of the one or more user selected fields within the application; analyzing a pre-existing, user provided data set of objects; training, based on the analysis, the predictive model; determining, for each user selected field based on the analysis, a confidence function for the predictive model that identifies the percentage of cases predicted correctly at different applied confidence levels, the percentage of cases predicted incorrectly at different applied confidence levels, and the percentage of cases in which the prediction model could not provide a prediction at different applied confidence levels; and providing a user interface for user review of the confidence functions for user selection of confidence threshold levels to be used with the predictive model.
公开/授权文献
信息查询