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 Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

This paper claims that a new field of empirical software engineering researchand practice is emerging: data mining using/used-by optimizers for empiricalstudies or DUO. For example, data miners can generate models that are exploredby optimizers. Also, optimizers can advise how to best adjust the controlparameters of a data miner. This combined approach acts like an agent leaningover the shoulder of an analyst that advises "ask this question next" or"ignore that problem, it is not relevant to your goals". Further, those agentscan help us build "better" predictive models, where "better" can be eithergreater predictive accuracy or faster modeling time (which, in turn, enablesthe exploration of a wider range of options). We also caution that the era ofpapers that just use data miners is coming to an end. Results obtained from anunoptimized data miner can be quickly refuted, just by applying an optimizer toproduce a different (and better performing) model. Our conclusion, hence, isthat for software analytics it is possible, useful and necessary to combinedata mining and optimization using DUO.

Better Software Analytics via "DUO": Data Mining Algorithms Using/Used-by Optimizers