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

A recent article proposed reduced mutual information for evaluation ofclustering, classification and community detection. The motivation is that thestandard normalized mutual information (NMI) may give counter-intuitive answersunder certain conditions and particularly when the number of clusters differsbetween the two divisions under consideration. The motivation makes sense.However, the examples given in the article are not accurate, and this commentdiscusses why. In addition, this comment also empirically demonstrates that thereduced mutual information cannot handle the difficulties of NMI and evenbrings more. The necessity of Kappa is also empirically validated in thiscomment.

Comment on "Improved mutual information measure for clustering, classification, and community detection"