Combining Predictors for Recommending Music:the False Positives’ approach to KDD Cup track 2

Suhrid Balakrishnan, Rensheng Wang, Carlos Scheidegger, Angus MacLellan, Yifan Hu, Aaron Archer, Shankar Krishnan, David Applegate, Guang Qin Ma, S. Tom Au
; Proceedings of KDD Cup 2011, PMLR 18:199-213, 2012.

Abstract

We describe our solution for the KDD Cup 2011 track 2 challenge. Our solution relies heavily on ensembling together diverse individual models for the prediction task, and achieved a final leaderboard/Test 1 misclassification rate of 3.8863%. This paper provides details on both the modeling and ensemble creation steps.

Cite this Paper


BibTeX
@InProceedings{pmlr-v18-balakrishnan12a, title = {Combining Predictors for Recommending Music:the False Positives’ approach to KDD Cup track 2}, author = {Suhrid Balakrishnan and Rensheng Wang and Carlos Scheidegger and Angus MacLellan and Yifan Hu and Aaron Archer and Shankar Krishnan and David Applegate and Guang Qin Ma and S. Tom Au}, booktitle = {Proceedings of KDD Cup 2011}, pages = {199--213}, year = {2012}, editor = {Gideon Dror and Yehuda Koren and Markus Weimer}, volume = {18}, series = {Proceedings of Machine Learning Research}, month = {21 Aug}, publisher = {PMLR}, pdf = {http://proceedings.mlr.press/v18/balakrishnan12a/balakrishnan12a.pdf}, url = {http://proceedings.mlr.press/v18/balakrishnan12a.html}, abstract = {We describe our solution for the KDD Cup 2011 track 2 challenge. Our solution relies heavily on ensembling together diverse individual models for the prediction task, and achieved a final leaderboard/Test 1 misclassification rate of 3.8863%. This paper provides details on both the modeling and ensemble creation steps.} }
Endnote
%0 Conference Paper %T Combining Predictors for Recommending Music:the False Positives’ approach to KDD Cup track 2 %A Suhrid Balakrishnan %A Rensheng Wang %A Carlos Scheidegger %A Angus MacLellan %A Yifan Hu %A Aaron Archer %A Shankar Krishnan %A David Applegate %A Guang Qin Ma %A S. Tom Au %B Proceedings of KDD Cup 2011 %C Proceedings of Machine Learning Research %D 2012 %E Gideon Dror %E Yehuda Koren %E Markus Weimer %F pmlr-v18-balakrishnan12a %I PMLR %J Proceedings of Machine Learning Research %P 199--213 %U http://proceedings.mlr.press %V 18 %W PMLR %X We describe our solution for the KDD Cup 2011 track 2 challenge. Our solution relies heavily on ensembling together diverse individual models for the prediction task, and achieved a final leaderboard/Test 1 misclassification rate of 3.8863%. This paper provides details on both the modeling and ensemble creation steps.
RIS
TY - CPAPER TI - Combining Predictors for Recommending Music:the False Positives’ approach to KDD Cup track 2 AU - Suhrid Balakrishnan AU - Rensheng Wang AU - Carlos Scheidegger AU - Angus MacLellan AU - Yifan Hu AU - Aaron Archer AU - Shankar Krishnan AU - David Applegate AU - Guang Qin Ma AU - S. Tom Au BT - Proceedings of KDD Cup 2011 PY - 2012/06/01 DA - 2012/06/01 ED - Gideon Dror ED - Yehuda Koren ED - Markus Weimer ID - pmlr-v18-balakrishnan12a PB - PMLR SP - 199 DP - PMLR EP - 213 L1 - http://proceedings.mlr.press/v18/balakrishnan12a/balakrishnan12a.pdf UR - http://proceedings.mlr.press/v18/balakrishnan12a.html AB - We describe our solution for the KDD Cup 2011 track 2 challenge. Our solution relies heavily on ensembling together diverse individual models for the prediction task, and achieved a final leaderboard/Test 1 misclassification rate of 3.8863%. This paper provides details on both the modeling and ensemble creation steps. ER -
APA
Balakrishnan, S., Wang, R., Scheidegger, C., MacLellan, A., Hu, Y., Archer, A., Krishnan, S., Applegate, D., Ma, G.Q. & Au, S.T.. (2012). Combining Predictors for Recommending Music:the False Positives’ approach to KDD Cup track 2. Proceedings of KDD Cup 2011, in PMLR 18:199-213

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