KnowledgePit Meets BrightBox: A Step Toward Insightful Investigation of the Results of Data Science Competitions

We discuss the benefits of integrating the KnowledgePit data science competition platform with the BrightBox technology aimed at diagnostics of machine learning models embedded within complex software systems. We briefly recall the history of international challenges held at KnowledgePit and we also...

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Bibliographic Details
Published in2022 17th Conference on Computer Science and Intelligence Systems (FedCSIS) Vol. 30; pp. 393 - 398
Main Authors Janusz, Andrzej, Slezak, Dominik
Format Conference Proceeding Journal Article
LanguageEnglish
Published Polish Information Processing Society 01.01.2022
Subjects
BrightBox technology
Data models
Data science
Data science competitions
Data visualization
Education
History
KnowledgePit platform
Machine learning
model stacking
Software systems
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ISSN2300-5963
DOI10.15439/2022F309

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Summary:We discuss the benefits of integrating the KnowledgePit data science competition platform with the BrightBox technology aimed at diagnostics of machine learning models embedded within complex software systems. We briefly recall the history of international challenges held at KnowledgePit and we also discuss in what sense such technologies as BrightBox can be helpful during the post-challenge analysis. In particular, we show how to combine solutions submitted by the competition participants in order to obtain even more accurate predictions. The discussed functionalities are of significant importance for the sponsors and organizers of data science / machine learning online contests because they support adoption of submissions while designing ultimate solutions of real-world problems.
ISSN:2300-5963
DOI:10.15439/2022F309