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

Linear regression is effective at identifying interpretable trends in a dataset, but averages out potentially different effects on subgroups within data.We propose an iterative algorithm based on the randomized Kaczmarz (RK) methodto automatically identify subgroups in data and perform linear regression onthese groups simultaneously. We prove almost sure convergence for this method,as well as linear convergence in expectation under certain conditions. Theresult is an interpretable collection of different weight vectors for theregressor variables that capture the different trends within data. Furthermore,we experimentally validate our convergence results by demonstrating the methodcan successfully identify two trends within simulated data.

Multi-Randomized Kaczmarz for Latent Class Regression