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Random forest

Known as: RF (disambiguation), Random forests, Random naive bayes 
Random forests or random decision forests are an ensemble learning method for classification, regression and other tasks, that operate by… Expand
Wikipedia

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2019
Highly Cited
2019
We propose generalized random forests, a method for non-parametric statistical estimation based on random forests (Breiman, 2001… Expand
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Highly Cited
2018
Highly Cited
2018
ABSTRACT Many scientific and engineering challenges—ranging from personalized medicine to customized marketing recommendations… Expand
Review
2016
Review
2016
Abstract A random forest (RF) classifier is an ensemble classifier that produces multiple decision trees, using a randomly… Expand
Highly Cited
2010
Highly Cited
2010
This paper proposes, focusing on random forests, the increasingly used statistical method for classification and regression… Expand
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Highly Cited
2009
Highly Cited
2009
Relative importance of regressor variables is an old topic that still awaits a satisfactory solution. When interest is in… Expand
Highly Cited
2008
Highly Cited
2008
Microarray studies yield data sets consisting of a large number of candidate predictors (genes) on a small number of observations… Expand
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Highly Cited
2007
Highly Cited
2007
We explore the problem of classifying images by the object categories they contain in the case of a large number of object… Expand
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Highly Cited
2006
Highly Cited
2006
Random Forests are considered for classification of multisource remote sensing and geographic data. Various ensemble… Expand
Highly Cited
2004
Highly Cited
2004
Random forests are a combination of tree predictors such that each tree depends on the values of a random vector sampled… Expand
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Highly Cited
2004
Highly Cited
2004
In this paper we propose two ways to deal with the imbalanced data classification problem using random forest. One is based on… Expand
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