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 proposes a new method to generate synthetic data sets based oncopula models. Our goal is to produce surrogate data resembling real data interms of marginal and joint distributions. We present a complete and reliablealgorithm for generating a synthetic data set comprising numeric or categoricalvariables. Applying our methodology to two datasets shows better performancecompared to other methods such as SMOTE and autoencoders.

Generation and Simulation of Synthetic Datasets with Copulas