公开(公告)号：US11526799B2

公开(公告)日：2022-12-13

申请号：US16264583

申请日：2019-01-31

Applicant: salesforce.com, inc.

Inventor： Kevin Moore ,  Leah McGuire ,  Eric Wayman ,  Shubha Nabar ,  Vitaly Gordon ,  Sarah Aerni

IPC: G06N20/00 ,  G06N5/04

Abstract: Methods and systems are provided to determine suitable hyperparameters for a machine learning model and/or feature engineering process. A suitable machine learning model and associated hyperparameters are determined by analyzing a dataset. Suitable hyperparameter values for compatible machine learning models having one or more hyperparameters in common and a compatible dataset schema are identified. Hyperparameters may be ranked according to each of their respective influences on a model performance metrics, and hyperparameter values identified as having greater influence may be more aggressively searched.

公开(公告)号：US20200057958A1

公开(公告)日：2020-02-20

申请号：US16264583

申请日：2019-01-31

Applicant: salesforce.com, inc.

Inventor： Kevin Moore ,  Leah McGuire ,  Eric Wayman ,  Shubha Nabar ,  Vitaly Gordon ,  Sarah Aerni

IPC: G06N20/00 ,  G06N5/04

Abstract: Methods and systems are provided to determine suitable hyperparameters for a machine learning model and/or feature engineering process. A suitable machine learning model and associated hyperparameters are determined by analyzing a dataset. Suitable hyperparameter values for compatible machine learning models having one or more hyperparameters in common and a compatible dataset schema are identified. Hyperparameters may be ranked according to each of their respective influences on a model performance metrics, and hyperparameter values identified as having greater influence may be more aggressively searched.