Invention Grant
- Patent Title: Network based machine learning generated simulations
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Application No.: US15844421Application Date: 2017-12-15
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Publication No.: US10693997B2Publication Date: 2020-06-23
- Inventor: Katherine Wright , Sepideh Hashtroodi , Teresa Hsin Yi Su , Flavia Moser , Sajjad Gholami , Zeyu Ni , Geoffrey Neil Peters
- Applicant: SAP SE
- Applicant Address: DE Waldorf
- Assignee: SAP SE
- Current Assignee: SAP SE
- Current Assignee Address: DE Waldorf
- Agency: Fountainhead Law Group P.C.
- Main IPC: H04L29/08
- IPC: H04L29/08 ; G06F40/14 ; G06F16/95 ; G06F16/958 ; G06N20/00 ; G06F16/248 ; G06F40/177

Abstract:
Embodiments of the present disclosure pertain to network based machine learning generated simulations. In one embodiment, the present disclosure includes a computer implemented method comprising sending first code comprising a programmable calculator from a server system to a client system across a network. A data request is sent to a database, the data request configured to retrieve data from the database comprising a plurality of fields and a target field. The retrieved data is processed using a machine learning algorithm to produce a weight for each field of the plurality of fields and a scoring data structure. The fields and the scoring data structure are sent to the client system across the network. A user selects values for the plurality of fields and the programmable calculator is configured based on the scoring data structure to generate a simulated value for the target field based on the user selected values.
Public/Granted literature
- US20190191009A1 NETWORK BASED MACHINE LEARNING GENERATED SIMULATIONS Public/Granted day:2019-06-20
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