Invention Grant
- Patent Title: Rejecting biased data using a machine learning model
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Application No.: US16126860Application Date: 2018-09-10
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Publication No.: US11250346B2Publication Date: 2022-02-15
- Inventor: Christopher Farrar , Steven Ross
- Applicant: Google LLC
- Applicant Address: US CA Mountain View
- Assignee: Google LLC
- Current Assignee: Google LLC
- Current Assignee Address: US CA Mountain View
- Agency: Hontgman LLP
- Agent Brett A. Krueger
- Main IPC: G06N20/00
- IPC: G06N20/00 ; G06N5/04

Abstract:
A method for rejecting biased data using a machine learning model includes receiving a cluster training data set including a known unbiased population of data and training a clustering model to segment the received cluster training data set into clusters based on data characteristics of the known unbiased population of data. Each cluster of the cluster training data set includes a cluster weight. The method also includes receiving a training data set for a machine learning model and generating training data set weights corresponding to the training data set for the machine learning model based on the clustering model. The method also includes adjusting each training data set weight of the training data set weights to match a respective cluster weight and providing the adjusted training data set to the machine learning model as an unbiased training data set.
Public/Granted literature
- US20200082300A1 Rejecting Biased Data Using a Machine Learning Model Public/Granted day:2020-03-12
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