$\chi$iplot: web-first visualisation platform for multidimensional data

Authors :: Tanaka, Akihiro
Tyree, Juniper
Björklund, Anton
Mäkelä, Jarmo
Puolamäki, Kai
Source :: Machine Learning and Knowledge Discovery in Databases: Applied Data Science and Demo Track. ECML PKDD 2023. Lecture Notes in Computer Science, vol 14175 pp. 335-339
Publication Year :: 2023
Abstract: $\chi$iplot is an HTML5-based system for interactive exploration of data and machine learning models. A key aspect is interaction, not only for the interactive plots but also between plots. Even though $\chi$iplot is not restricted to any single application domain, we have developed and tested it with domain experts in quantum chemistry to study molecular interactions and regression models. $\chi$iplot can be run both locally and online in a web browser (keeping the data local). The plots and data can also easily be exported and shared. A modular structure also makes $\chi$iplot optimal for developing machine learning and new interaction methods.<br />Comment: 5 pages, 1 figure, accepted to the demo track of ECML PKDD 2023, https://github.com/edahelsinki/xiplot

Subjects :: Computer Science - Human-Computer Interaction
Computer Science - Computational Engineering, Finance, and Science
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Database :: arXiv
Journal :: Machine Learning and Knowledge Discovery in Databases: Applied Data Science and Demo Track. ECML PKDD 2023. Lecture Notes in Computer Science, vol 14175 pp. 335-339
Publication Type :: Report
Accession number :: edsarx.2306.12110
Document Type :: Working Paper
Full Text :: https://doi.org/10.1007/978-3-031-43430-3_26