Elements of an Automatic Data ScientistShow others and affiliations
2018 (English)In: Advances in Intelligent Data Analysis XVII / [ed] Wouter Duivesteijn, Arno Siebes, Antti Ukkonen, Cham: Springer International Publishing , 2018, Vol. 11191Conference paper, Published paper (Refereed)
Abstract [en]
A simple but non-trivial setting for automating data science is introduced. Given are a set of worksheets in a spreadsheet and the goal is to automatically complete some values. We also outline elements of the Synth framework that tackles this task: Synth-a-Sizer, an automated data wrangling system for automatically transforming the problem into attribute-value format; TacLe, an inductive constraint learning system for inducing formulas in spreadsheets; Mercs, a versatile predictive learning system; as well as the autocompletion component that integrates these systems.
Place, publisher, year, edition, pages
Cham: Springer International Publishing , 2018. Vol. 11191
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 11191
Keywords [en]
Automated data science, Autocompletion, Data wrangling, Learning constraints, Versatile models
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:oru:diva-87428DOI: 10.1007/978-3-030-01768-2_1ISI: 000719688600001Scopus ID: 2-s2.0-85055720101ISBN: 978-3-030-01767-5 (print)ISBN: 978-3-030-01768-2 (electronic)OAI: oai:DiVA.org:oru-87428DiVA, id: diva2:1501552
Conference
17th International Symposium (IDA 2018), ’s-Hertogenbosch, The Netherlands, October 24–26, 2018
2020-11-172020-11-172021-12-30Bibliographically approved