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

Code comments are vital to source code as they help developers with programcomprehension tasks. Written in natural language (usually English), codecomments convey a variety of different information, which are grouped intospecific categories. In this study, we construct 19 binary machine learningclassifiers for code comment categories that belong to three differentprogramming languages. We present a comparison of performance scores fordifferent types of machine learning classifiers and show that the Linear SVCclassifier has the highest average F1 score of 0.5474.

Performance Comparison of Binary Machine Learning Classifiers in Identifying Code Comment Types: An Exploratory Study