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 Tools annual

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 Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Machine learning is a promising approach to visualization recommendation dueto its high scalability and representational power. Researchers can create aneural network to predict visualizations from input data by training it over acorpus of datasets and visualization examples. However, these machine learningmodels can reflect trends in their training data that may negatively affecttheir performance. Our research project aims to address training bias inmachine learning visualization recommendation systems by identifying trends inthe training data through statistical analysis.

Addressing Bias in Visualization Recommenders by Identifying Trends in  Training Data: Improving VizML Through a Statistical Analysis of the Plotly  Community Feed