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Tracking Cloud Forests With Cloud Technology and Random Forests
Frontiers in Environmental Science, 2021 Hotspots of endemic biodiversity, tropical cloud forests teem with ecosystem services such as drinking water, food, building materials, and carbon sequestration. Unfortunately, already threatened by climate change, the cloud forests in our study area are
Pasky Pascual, Cam Pascual
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Generalized random forests [PDF]
The Annals of Statistics, 2019 We propose generalized random forests, a method for non-parametric statistical estimation based on random forests (Breiman, 2001) that can be used to fit any quantity of interest identified as the solution to a set of local moment equations. Following the literature on local maximum likelihood estimation, our method considers a weighted set of nearby ...
Athey, Susan +2 more
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Bioinformatics, 2008 Abstract Although the random forest classification procedure works well in datasets with many features, when the number of features is huge and the percentage of truly informative features is small, such as with DNA microarray data, its performance tends to decline significantly.
Dhammika, Amaratunga +2 more
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Multi-Class Assessment Based on Random Forests
Education Sciences, 2021 Today, many students are moving towards higher education courses that do not suit them and end up failing. The purpose of this study is to help provide counselors with better knowledge so that they can offer future students courses corresponding to their
Mehdi Berriri +3 more
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A Novel Consistent Random Forest Framework: Bernoulli Random Forests [PDF]
IEEE Transactions on Neural Networks and Learning Systems, 2018 Random forests (RFs) are recognized as one type of ensemble learning method and are effective for the most classification and regression tasks. Despite their impressive empirical performance, the theory of RFs has yet been fully proved. Several theoretically guaranteed RF variants have been presented, but their poor practical performance has been ...
Yisen Wang +4 more
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Using random forests to model 90-day hometime in people with stroke
BMC Medical Research Methodology, 2021 Background Ninety-day hometime, the number of days a patient is living in the community in the first 90 after stroke, exhibits a non-normal bucket-shaped distribution, with lower and upper constraints making its analysis difficult.
Jessalyn K. Holodinsky +3 more
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Evaluation of random forests and Prophet for daily streamflow forecasting [PDF]
Advances in Geosciences, 2018 We assess the performance of random forests and Prophet in forecasting daily streamflow up to seven days ahead in a river in the US. Both the assessed forecasting methods use past streamflow observations, while random forests additionally use past ...
G. A. Papacharalampous +3 more
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Random two-component spanning forests [PDF]
, 2014 We study random two-component spanning forests ($2$SFs) of finite graphs, giving formulas for the first and second moments of the sizes of the components, vertex-inclusion probabilities for one or two vertices, and the probability that an edge separates ...
Kassel, Adrien, Kenyon, Richard, Wu, Wei
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Machine Learning, 2001 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Improving random forest predictions in small datasets from two-phase sampling designs
BMC Medical Informatics and Decision Making, 2021 Background While random forests are one of the most successful machine learning methods, it is necessary to optimize their performance for use with datasets resulting from a two-phase sampling design with a small number of cases—a common situation in ...
Sunwoo Han +2 more
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