LogitBoost

In machine learning and computational learning theory, LogitBoost is a boosting algorithm formulated by Jerome Friedman, Trevor Hastie, and Robert… (More)
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Papers overview

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2017
2017
The rapid growth in the volume and importance of web communication throughout the Internet has heightened the need for better… (More)
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2014
2014
LogitBoost, MART and their variant can be viewed as additive tree regression using logistic loss and boosting style optimization… (More)
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2013
2013
Mitigation of credit risk is a key aspect of portfolio management in any financial institution. This is primarily due to… (More)
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2012
2012
This paper presents an improvement to model learning when using multi-class LogitBoost for classification. Motivated by the… (More)
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Highly Cited
2010
Highly Cited
2010
Logitboost is an influential boosting algorithm for classification. In this paper, we develop robust logitboost to provide an… (More)
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2009
2009
We develop abc-logitboost, based on the prior work on abc-boost[10] and robust logitboost[11]. Our extensive experiments on a… (More)
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2006
2006
Recently, Adaboost has been compared to greedy backfitting of extended additive models in logistic regression problems, or… (More)
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2006
2006
Automated text classification has been considered as a vital method to manage and process a vast amount of documents in digital… (More)
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2006
2006
We apply LogitBoost with a tree-based learner to the five WCCI 2006 performance prediction challenge datasets. The number of… (More)
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2005
2005
The ensembles of simple Bayesian classifiers have traditionally not been a focus of research. The reason is that simple Bayes is… (More)
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