Invention Grant
- Patent Title: Selecting attributes by progressive sampling to generate digital predictive models
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Application No.: US15388922Application Date: 2016-12-22
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Publication No.: US10885441B2Publication Date: 2021-01-05
- Inventor: Wei Zhang , Scott Tomko
- Applicant: Adobe Inc.
- Applicant Address: US CA San Jose
- Assignee: Adobe Inc.
- Current Assignee: Adobe Inc.
- Current Assignee Address: US CA San Jose
- Agency: Keller Jolley Preece
- Main IPC: G06N5/02
- IPC: G06N5/02 ; G06N20/00 ; G06N5/00

Abstract:
The present disclosure includes methods and systems for generating digital predictive models by progressively sampling a repository of data samples. In particular, one or more embodiments of the disclosed systems and methods identify initial attributes for predicting a target attribute and utilize the initial attributes to identify a coarse sample set. Moreover, the disclosed systems and methods can utilize the coarse sample set to identify focused attributes pertinent to predicting the target attribute. Utilizing the focused attributes, the disclosed systems and methods can identify refined data samples and utilize the refined data samples to identify final attributes and generate a digital predictive model.
Public/Granted literature
- US20180181869A1 SELECTING ATTRIBUTES BY PROGRESSIVE SAMPLING TO GENERATE DIGITAL PREDICTIVE MODELS Public/Granted day:2018-06-28
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