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Improved random forest classification model combined with C5.0 algorithm for vegetation feature analysis in non-agricultural environments
In response to the challenges posed by the high computational complexity and suboptimal classification performance of traditional random forest...
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Random forest method for estimation of brake specific fuel consumption
The internal combustion engine is a widely used power equipment in various fields, and its energy utilization is measured using brake specific fuel...
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Mental health and natural land cover: a global analysis based on random forest with geographical consideration
Natural features in living environments can help to reduce stress and improve mental health. Different land types have disproportionate impacts on...
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Detection of atmospheric radon concentration anomalies and their potential for earthquake prediction using Random Forest analysis
Various anomalies occurring before earthquakes are currently being studied to predict seismic events, with one of them being the radioactive element...
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COVID-19 mortality prediction in Hungarian ICU settings implementing random forest algorithm
The emergence of newer SARS-CoV-2 variants of concern (VOCs) profoundly changed the ICU demography; this shift in the virus’s genotype and its...
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Multi-source information fusion-driven corn yield prediction using the Random Forest from the perspective of Agricultural and Forestry Economic Management
The objective of this study is to promptly and accurately allocate resources, scientifically guide grain distribution, and enhance the precision of...
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Hybrid model for precise hepatitis-C classification using improved random forest and SVM method
Hepatitis C Virus (HCV) is a viral infection that causes liver inflammation. Annually, approximately 3.4 million cases of HCV are reported worldwide....
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Source discrimination of mine water based on the random forest method
Machine learning is one of the widely used techniques to pattern recognition. Use of the machine learning tools is becoming a more accessible...
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Monitoring of carbon-water fluxes at Eurasian meteorological stations using random forest and remote sensing
Simulating the carbon-water fluxes at more widely distributed meteorological stations based on the sparsely and unevenly distributed eddy covariance...
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Random forest differentiation of Escherichia coli in elderly sepsis using biomarkers and infectious sites
This study addresses the challenge of accurately diagnosing sepsis subtypes in elderly patients, particularly distinguishing between Escherichia coli...
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A hybrid CNN-Random Forest algorithm for bacterial spore segmentation and classification in TEM images
We present a new approach to segment and classify bacterial spore layers from Transmission Electron Microscopy (TEM) images using a hybrid...
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Assessing the influence of landscape conservation and protected areas on social wellbeing using random forest machine learning
The urgency of interconnected social-ecological dilemmas such as rapid biodiversity loss, habitat loss and fragmentation, and the escalating climate...
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Alternative stop** rules to limit tree expansion for random forest models
Random forests are a popular type of machine learning model, which are relatively robust to overfitting, unlike some other machine learning models,...
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Computational intelligence modeling of hyoscine drug solubility and solvent density in supercritical processing: gradient boosting, extra trees, and random forest models
This work presents the results of using tree-based models, including Gradient Boosting, Extra Trees, and Random Forest, to model the solubility of...
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Selection and prediction of metro station sites based on spatial data and random forest: a study of Lanzhou, China
Urban economic development, congestion relief, and traffic efficiency are all greatly impacted by the thoughtful planning of urban metro station...
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Differential diagnosis of thyroid nodule capsules using random forest guided selection of image features
Microscopic evaluation of tissue sections stained with hematoxylin and eosin is the current gold standard for diagnosing thyroid pathology. Digital...
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Hybridized KNN-Random Forest Algorithm: Image Demosaicing with Reduced Artifacts
Demosaicing is a necessary step in the image processing process in many digital colour cameras. The demosaicing approach creates a full-colour image...
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Multi-hazard exposure map** under climate crisis using random forest algorithm for the Kalimantan Islands, Indonesia
Numerous natural disasters that threaten people’s lives and property occur in Indonesia. Climate change-induced temperature increases are expected to...
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Map** livestock density distribution in the Selenge River Basin of Mongolia using random forest
Map** dynamically distributed livestock in the vast steppe area based on statistical data collected by administrative units is very difficult as it...
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Bootstrap** random forest and CHAID for prediction of white spot disease among shrimp farmers
Technology is playing an important role is healthcare particularly as it relates to disease prevention and detection. This is evident in the COVID-19...
