Title :
Data Prediction Competitions -- Far More than Just a Bit of Fun
Author :
Goldbloom, Anthony
Author_Institution :
Kaggle, Melbourne, VIC, Australia
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;
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
DOI :
10.1109/ICDMW.2010.56
