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method algorithm » network algorithm (Expand Search), means algorithm (Expand Search), mean algorithm (Expand Search)
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forests using » tests using (Expand Search), stress using (Expand Search), rest using (Expand Search)
element » elements (Expand Search)
method algorithm » network algorithm (Expand Search), means algorithm (Expand Search), mean algorithm (Expand Search)
coding algorithm » cosine algorithm (Expand Search), modeling algorithm (Expand Search), finding algorithm (Expand Search)
using algorithm » using algorithms (Expand Search), routing algorithm (Expand Search), fusion algorithm (Expand Search)
forests using » tests using (Expand Search), stress using (Expand Search), rest using (Expand Search)
element » elements (Expand Search)
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Improved random forest algorithm.
Published 2025“…Compared with MDA-RF, the prediction accuracy of the improved RF built on the same subset increased by 1.7%, indicating that improving the bootstrap sampling of random forest by using the K-means++ clustering algorithm can enhance model accuracy to some extent. …”
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Feature selection using Boruta algorithm.
Published 2025“…Feature selection was performed using the Boruta algorithm and model performance was evaluated by comparing accuracy, precision, recall, F1 score, MCC, Cohen’s Kappa and AUROC.…”
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Pseudocode for the missForestPredict algorithm.
Published 2025“…The algorithm iteratively imputes variables using random forests until a convergence criterion, unified for continuous and categorical variables, is met. …”
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The schematic diagram of the iForest algorithm.
Published 2025“…Subsampling and cross factor are designed and used to overcome the shortcomings of the isolated forest algorithm (iForest). …”
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TreeMap 2016 Forest Type Algorithm (Image Service)
Published 2024“…We used a random forests machine-learning algorithm to impute the forest plot data to a set of target rasters provided by Landscape Fire and Resource Management Planning Tools (LANDFIRE: https://landfire.gov). …”
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Image 9_Using a random forest model to predict volume growth of larch, birch, and their mixed forests in northern China.jpeg
Published 2025“…Using data from the National Forest Inventory (NFI), plot-level measurements, and environmental variables from pure larch (LP), birch (BP), and mixed larch-birch (LB) forests in the mountainous region of northern Hebei, China, this study employed random forest (RF) algorithms to evaluate the relative importance and partial dependence of biotic and abiotic factors on stand volume growth. …”
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Table 1_Using a random forest model to predict volume growth of larch, birch, and their mixed forests in northern China.docx
Published 2025“…Using data from the National Forest Inventory (NFI), plot-level measurements, and environmental variables from pure larch (LP), birch (BP), and mixed larch-birch (LB) forests in the mountainous region of northern Hebei, China, this study employed random forest (RF) algorithms to evaluate the relative importance and partial dependence of biotic and abiotic factors on stand volume growth. …”