International Business Machines Corporation
ENSEMBLE MACHINE LEARNING MODEL

Last updated:

Abstract:

Described are techniques for using a dynamic ensemble model. The techniques including training a plurality of machine learning models on training data. The techniques further include identifying a similar subset of the training data that is similar to a dataset for evaluation. The techniques further include assembling a subset of models from the plurality of machine learning models based on performance of the subset of models on the similar subset of the training data. The techniques further include generating an output from the subset of models for the dataset for evaluation.

Status:
Application
Type:

Utility

Filling date:

19 Oct 2020

Issue date:

21 Apr 2022