Predicting customer behaviour: The University of Melbourne’s KDD Cup report

Hugh Miller, Sandy Clarke, Stephen Lane, Andrew Lonie, David Lazaridis, Slave Petrovski, Owen Jones
Proceedings of KDD-Cup 2009 Competition, PMLR 7:45-55, 2009.

Abstract

We discuss the challenges of the 2009 KDD Cup along with our ideas and methodologies for modelling the problem. The main stages included aggressive nonparametric feature selection, careful treatment of categorical variables and tuning a gradient boosting machine under Bernoulli loss with trees.

Cite this Paper

BibTeX
@InProceedings{pmlr-v7-miller09, title = {Predicting customer behaviour: The University of Melbourne's KDD Cup report}, author = {Miller, Hugh and Clarke, Sandy and Lane, Stephen and Lonie, Andrew and Lazaridis, David and Petrovski, Slave and Jones, Owen}, booktitle = {Proceedings of KDD-Cup 2009 Competition}, pages = {45--55}, year = {2009}, editor = {Dror, Gideon and Boullé, Mar and Guyon, Isabelle and Lemaire, Vincent and Vogel, David}, volume = {7}, series = {Proceedings of Machine Learning Research}, address = {New York, New York, USA}, month = {28 Jun}, publisher = {PMLR}, pdf = {http://proceedings.mlr.press/v7/miller09/miller09.pdf}, url = {https://proceedings.mlr.press/v7/miller09.html}, abstract = {We discuss the challenges of the 2009 KDD Cup along with our ideas and methodologies for modelling the problem. The main stages included aggressive nonparametric feature selection, careful treatment of categorical variables and tuning a gradient boosting machine under Bernoulli loss with trees.} }
Endnote
%0 Conference Paper %T Predicting customer behaviour: The University of Melbourne’s KDD Cup report %A Hugh Miller %A Sandy Clarke %A Stephen Lane %A Andrew Lonie %A David Lazaridis %A Slave Petrovski %A Owen Jones %B Proceedings of KDD-Cup 2009 Competition %C Proceedings of Machine Learning Research %D 2009 %E Gideon Dror %E Mar Boullé %E Isabelle Guyon %E Vincent Lemaire %E David Vogel %F pmlr-v7-miller09 %I PMLR %P 45--55 %U https://proceedings.mlr.press/v7/miller09.html %V 7 %X We discuss the challenges of the 2009 KDD Cup along with our ideas and methodologies for modelling the problem. The main stages included aggressive nonparametric feature selection, careful treatment of categorical variables and tuning a gradient boosting machine under Bernoulli loss with trees.
RIS
TY - CPAPER TI - Predicting customer behaviour: The University of Melbourne’s KDD Cup report AU - Hugh Miller AU - Sandy Clarke AU - Stephen Lane AU - Andrew Lonie AU - David Lazaridis AU - Slave Petrovski AU - Owen Jones BT - Proceedings of KDD-Cup 2009 Competition DA - 2009/12/04 ED - Gideon Dror ED - Mar Boullé ED - Isabelle Guyon ED - Vincent Lemaire ED - David Vogel ID - pmlr-v7-miller09 PB - PMLR DP - Proceedings of Machine Learning Research VL - 7 SP - 45 EP - 55 L1 - http://proceedings.mlr.press/v7/miller09/miller09.pdf UR - https://proceedings.mlr.press/v7/miller09.html AB - We discuss the challenges of the 2009 KDD Cup along with our ideas and methodologies for modelling the problem. The main stages included aggressive nonparametric feature selection, careful treatment of categorical variables and tuning a gradient boosting machine under Bernoulli loss with trees. ER -
APA
Miller, H., Clarke, S., Lane, S., Lonie, A., Lazaridis, D., Petrovski, S. & Jones, O.. (2009). Predicting customer behaviour: The University of Melbourne’s KDD Cup report. Proceedings of KDD-Cup 2009 Competition, in Proceedings of Machine Learning Research 7:45-55 Available from https://proceedings.mlr.press/v7/miller09.html.

Related Material