Hybrid Machine Learning
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United States of America
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Issued Date -
Mar 20, 2025
app pub date -
Nov 29, 2024
filing date -
Nov 29, 2024
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Abstract
A predictive computational model is generated through a hybrid process. In the hybrid process, a trained predictive computational model is automatically generated based on a dataset, where the predictive computational model is trained to generate an output based on new data. The automatic process uses a pipeline to train the model and makes decisions in the steps of the pipeline. After the model is automatically trained, a representation of the pipeline is 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 generate an output based on new data.
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