Bayesian network model structure based on binary evolutionary algorithm.

ABSTRACT: With the continuous development of new technologies, the scale of training data is also expanding. Machine learning algorithms are gradually beginning to be studied and applied in places where the scale of data is relatively large. Because the current structure of learning algorithms only focus on the identification of dependencies and ignores the direction of dependencies, it causes multiple labeled samples not to identify categories. Multiple labels need to be classified using techniques such as machine learning and then applied to solve the problem. In the environment of more training data, it is very meaningful to explore the structure extension to identify the dependencies between attributes and take into account the direction of dependencies. In this article, Bayesian network structu

SUBMITTER: Yao Y 

PROVIDER: S-EPMC10403175 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature