English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

This paper uses Gaussian mixture model instead of linear Gaussian model tofit the distribution of every node in Bayesian network. We will explain why andhow we use Gaussian mixture models in Bayesian network. Meanwhile we propose anew method, called double iteration algorithm, to optimize the mixture model,the double iteration algorithm combines the expectation maximization algorithmand gradient descent algorithm, and it performs perfectly on the Bayesiannetwork with mixture models. In experiments we test the Gaussian mixture modeland the optimization algorithm on different graphs which is generated bydifferent structure learning algorithm on real data sets, and give the detailsof every experiment.

Gaussian mixture modeling of nodes in Bayesian network according to maximal parental cliques