- 专利标题: Machine-learning model to predict probability of success of an operator in a PaaS cloud environment
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申请号: US16950228申请日: 2020-11-17
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公开(公告)号: US12124924B2公开(公告)日: 2024-10-22
- 发明人: Ali Kanso , Jinho Hwang , Muhammed Fatih Bulut , Shripad Nadgowda , Chen Lin
- 申请人: International Business Machines Corporation
- 申请人地址: US NY Armonk
- 专利权人: INTERNATIONAL BUSINESS MACHINES CORPORATION
- 当前专利权人: INTERNATIONAL BUSINESS MACHINES CORPORATION
- 当前专利权人地址: US NY Armonk
- 代理机构: Amin, Turocy & Watson, LLP
- 主分类号: G06N20/00
- IPC分类号: G06N20/00 ; G06F8/60 ; G06F8/61 ; G06N7/01 ; H04L41/50
摘要:
Systems and methods are provided that integrate a machine-learning model, and more specifically, utilizing a platform as a service (PaaS) cloud to predict probability of success for an operator in an environment. An embodiment comprises a system having: a processor that executes computer executable components stored in memory, trained machine-learning model that predicts probability of success for deployment of an operator in an environment with a namespace of a platform as a service (PaaS) cloud, and a deployment component that receives a first operator and a first namespace and employs the trained machine-learning model to predict success of deployment of the first operator in a first environment.
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