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

Outlier is the term that indicates in statistics an anomalous observation,aberrant, clearly distant from others collected observations. The outliers arethe subject to animated discussions in various contexts with regard to be ornot to be considered in the average evaluations. Outliers can become a precioussource of information, on condition that be able to accurately identify thepresence in the reference datasets. The need to identify the presence ofclustered outliers in a dataset not previously treated could argue for a fuzzyclustering, emphasized by using the quadratic Euclidean distance as similaritymeasure. For interesting and useful results, it should be inclined apossibilistic clustering approach, where the term 'possibilistic' means, alwaysin mathematical rigor, a component of interpretation of values that point outanomalous cases. The crisp method does not allow it, the fuzzy method introduceit, the possibilistic one use it. This is a very simple paper with divulgativepurposes, addressed especially to students, but not only.

Outliers Emphasis on Cluster Analysis - The use of squared Euclidean distance and fuzzy clustering to detect outliers in a dataset