Adobe Inc.
Categorical data transformation and clustering for machine learning using data repository systems
Last updated:
Abstract:
Categorical data transformation and clustering techniques and systems are described for machine learning. These techniques and systems are configured to improve operation of a computing device to support efficient and accurate use of categorical data, which is not possible using conventional techniques. In an example, categorical data is received by a computing device that includes a categorical variable having a non-numerical data type for a number of classes. The categorical data is then converted into numerical data based on clustering used to generate a plurality of latent classes.
Status:
Grant
Type:
Utility
Filling date:
16 Mar 2018
Issue date:
15 Jun 2021