The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Jan. 07, 2025

Filed:

Aug. 25, 2020
Applicant:

Alteryx, Inc., Irvine, CA (US);

Inventors:

Dylan Blanchard, Chicago, IL (US);

Tyler Heinl, Denver, CO (US);

Roland Manfred Hochmuth, Fort Collins, CO (US);

Assignee:

Alteryx, Inc., Irvine, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 5/04 (2023.01); G06F 16/9032 (2019.01); G06F 16/9035 (2019.01); G06F 18/21 (2023.01); G06F 18/2113 (2023.01); G06F 18/214 (2023.01); G06F 18/22 (2023.01); G06N 3/096 (2023.01); G06N 3/0985 (2023.01); G06N 3/10 (2006.01); G06N 5/045 (2023.01); G06N 20/00 (2019.01);
U.S. Cl.
CPC ...
G06N 5/04 (2013.01); G06F 16/90328 (2019.01); G06F 18/2113 (2023.01); G06F 18/214 (2023.01); G06F 18/2178 (2023.01); G06F 18/22 (2023.01); G06N 3/096 (2023.01); G06N 3/0985 (2023.01); G06N 3/10 (2013.01); G06N 5/045 (2013.01); G06N 20/00 (2019.01); G06F 16/9035 (2019.01);
Abstract

A model is trained through a hybrid machine learning process. In the hybrid machine landing process, an automatic machine learning process is performed on a dataset to generate a model for making a prediction. The automatic machine learning process uses a pipeline to train the model and makes decisions in the steps of the pipeline. After the model is trained through the automatic machine learning process, a representation of the pipeline is generated and presented to a user in a user interface. The user interface allows the user to modify at least some decision made in the automatic machine learning process. One or more modifications are received from the user through the user interface and are used to refine the trained model. The refined model is deployed to make the prediction based on new data.


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