DocumentCode
2195022
Title
Data Prediction Competitions -- Far More than Just a Bit of Fun
Author
Goldbloom, Anthony
Author_Institution
Kaggle, Melbourne, VIC, Australia
fYear
2010
fDate
13-13 Dec. 2010
Firstpage
1385
Lastpage
1386
Abstract
Data prediction competitions facilitate a step change in the evolution of analytics outsourcing. They offer companies and researchers a cost effective way to harness the `cognitive surplus´ of data scientists who are hungry for real-world data and motivated to excel whatever the prize. Competitions are effective because there are any number of techniques that can be applied to any modeling problem but we can´t know in advance which will be most effective. By exposing the problem to a wide audience, competitions are an effective way to reach the frontier of what is possible from a given dataset.
Keywords
data mining; analytics outsourcing; cognitive surplus; data prediction competition; bioinformatics; competitions; crowdsourcing; data mining; machine learning; statistics;
fLanguage
English
Publisher
ieee
Conference_Titel
Data Mining Workshops (ICDMW), 2010 IEEE International Conference on
Conference_Location
Sydney, NSW
Print_ISBN
978-1-4244-9244-2
Electronic_ISBN
978-0-7695-4257-7
Type
conf
DOI
10.1109/ICDMW.2010.56
Filename
5693459
Link To Document