US 2022/0067541 A1 · HYBRID MACHINE LEARNING

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.

Claims20

Dependent claims

A computer implemented method, comprising:

receiving a dataset;
performing an automatic machine learning process on the received dataset to train a model for making a prediction based on new data, the automatic machine learning process comprising making a sequence of decisions based on a pipeline;
after the model is trained, generating a representation of the pipeline;
providing the representation of the pipeline for display in a user interface, the user interface allowing a user to modify at least some of the decisions made in the automatic machine learning process;
receiving one or more modifications from the user through the user interface;
and
refining the model based on the one or more modifications from the user, the refined model to be used to make the prediction based on new data.

4 more elements

A non-transitory computer-readable memory storing executable computer program instructions for processing data blocks in a data analytics system, the instructions executable to perform operations comprising:

receiving a dataset;
performing an automatic machine learning process on the received dataset to train a model for making a prediction based on new data, the automatic machine learning process comprising making a sequence of decisions based on a pipeline;
after the model is trained, generating a representation of the pipeline;
providing the representation of the pipeline for display in a user interface, the user interface allowing a user to modify at least some of the decisions made in the automatic machine learning process;
receiving one or more modifications from the user through the user interface;
and
refining the model based on the one or more modifications from the user, the refined model to be used to make the prediction based on new data.

4 more elements

A system, comprising:

a computer processor for executing computer program instructions;
and
a non-transitory computer-readable memory storing computer program instructions executable by the computer processor to perform operations comprising:
receiving a dataset;
performing an automatic machine learning process on the received dataset to train a model for making a prediction based on new data, the automatic machine learning process comprising making a sequence of decisions based on a pipeline;
after the model is trained, generating a representation of the pipeline;
providing the representation of the pipeline for display in a user interface, the user interface allowing a user to modify at least some of the decisions made in the automatic machine learning process;
receiving one or more modifications from the user through the user interface;
and
refining the model based on the one or more modifications from the user, the refined model to be used to make the prediction based on new data.

7 more elements

Dependencies are inferred from the claim text.

Hybrid machine learning

Life of this patent

Hybrid machine learning

Life of this patent

Abstract

Claims20