%0 Journal Article %1 borisov_zero-inflated_2009 %A Borisov, Alexander %A Runger, G. %A Tuv, E. %A Lurponglukana-Strand, Nutta %D 2009 %J Advances in Intelligent Data Analysis VIII %K Boosting, Learning, Machine Poisson, \_tablet, inflated regression trees, zero %P 225--236 %R 10.1007/978-3-642-03915-7_20 %T Zero-inflated boosted ensembles for rare event counts %U http://www.springerlink.com/index/5006gt8610u040u3.pdf %V 5572 %X Two linked ensembles are used for a supervised learning problem with rare-event counts. With many target instances of zero, more traditional loss functions (such as squared error and class error) are often not relevant and a statistical model leads to a likelihood with two related parameters from a zero-inflated Poisson (ZIP) distribution. In a new approach, a linked pair of gradient boosted tree ensembles are developed to handle the multiple parameters in a manner that can be generalized to other problems. The result is a unique learner that extends machine learning methods to data with nontraditional structures. We empirically compare to two real data sets and two artificial data sets versus a single-tree approach (ZIP-tree) and a statistical generalized linear model.

@article{borisov_zero-inflated_2009, abstract = {Two linked ensembles are used for a supervised learning problem with rare-event counts. With many target instances of zero, more traditional loss functions (such as squared error and class error) are often not relevant and a statistical model leads to a likelihood with two related parameters from a zero-inflated Poisson (ZIP) distribution. In a new approach, a linked pair of gradient boosted tree ensembles are developed to handle the multiple parameters in a manner that can be generalized to other problems. The result is a unique learner that extends machine learning methods to data with nontraditional structures. We empirically compare to two real data sets and two artificial data sets versus a single-tree approach (ZIP-tree) and a statistical generalized linear model.}, added-at = {2017-01-09T13:57:26.000+0100}, author = {Borisov, Alexander and Runger, G. and Tuv, E. and Lurponglukana-Strand, Nutta}, biburl = {https://www.bibsonomy.org/bibtex/23df54c8714ffe32d0a619256366bf318/yourwelcome}, doi = {10.1007/978-3-642-03915-7_20}, interhash = {5b9d7b89dd4d5faf1a67a7c54a2d6916}, intrahash = {3df54c8714ffe32d0a619256366bf318}, journal = {Advances in Intelligent Data Analysis VIII}, keywords = {Boosting, Learning, Machine Poisson, \_tablet, inflated regression trees, zero}, pages = {225--236}, timestamp = {2017-01-09T14:01:11.000+0100}, title = {Zero-inflated boosted ensembles for rare event counts}, url = {http://www.springerlink.com/index/5006gt8610u040u3.pdf}, urldate = {2012-08-04}, volume = 5572, year = 2009 }