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LogitBoost

In machine learning and computational learning theory, LogitBoost is a boosting algorithm formulated by Jerome Friedman, Trevor Hastie, and Robert… 
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Related topics

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14 relations
AdaBoostBoosting (machine learning)BrownBoostComputational learning theory

Broader (1)

Ensemble learning

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2018
2018
Machine learning: Probabilistic methods
2017
2017
The utilisation of machine learning approaches for medical data classification and personal care system mangementfor sickle cell disease
The expert systems and smart devices played a key role in the development of health care in terms of continuous monitoring of… 
2017
2017
BVDT: A Boosted Vector Decision Tree Algorithm for Multi-Class Classification Problems
In this paper, we propose a powerful weak learner (Vector Decision Tree (VDT)) and a new Boosted Vector Decision Tree (BVDT… 
2015
2015
Self-Train LogitBoost for Semi-supervised Learning
Semi-supervised classification methods are based on the use of unlabeled data in combination with a smaller set of labeled… 
2013
2013
Improved Boosting Performance by Explicit Handling of Ambiguous Positive Examples
Visual classes naturally have ambiguous examples, that are different depending on feature and classifier and are hard to… 
2013
2013
Improved Boosting Performance by Exclusion of Ambiguous Positive Examples
In visual object class recognition it is difficult to densely sample the set of positive examples. Therefore, frequently there… 
2010
2010
Early stopping in L 2 Boosting
It is well known that the boosting-like algorithms, such as AdaBoost and many of its modifications, may over-fit the training… 
2009
2009
Multi-resolution boosting for classification and regression problems
Various forms of additive modeling techniques have been successfully used in many data mining and machine learning–related… 
2007
2007
Automatic Recognition of Craters on the Surface of Mars Based on Boosting Techniques
The identification of impact craters on a planetary surface has crucial importance for planetary studies because it allows the… 
2006
2006
Contextual Image Classification Based on Spatial Boosting
  • R. Nishii
  • IEEE International Symposium on Geoscience and…
  • 2006
  • Corpus ID: 31460394
Spatial AdaBoost proposed by Nishii and Eguchi (TGRS, 2005) is a supervised image classification method. It is a voting machine… 
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