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 describes our efforts in predicting current and futurepsychological health from childhood essays within the scope of the CLPsych-2018Shared Task. We experimented with a number of different models, includingrecurrent and convolutional networks, Poisson regression, support vectorregression, and L1 and L2 regularized linear regression. We obtained the bestresults on the training/development data with L2 regularized linear regression(ridge regression) which also got the best scores on main metrics in theofficial testing for task A (predicting psychological health from essayswritten at the age of 11 years) and task B (predicting later psychologicalhealth from essays written at the age of 11).

T\"ubingen-Oslo system: Linear regression works the best at Predicting  Current and Future Psychological Health from Childhood Essays in the CLPsych  2018 Shared Task