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Random Forest
In this chapter, another machine learning algorithm called Random Forest will be considered. As data-driven performance analysis in sports is... -
Data-driven multinomial random forest: a new random forest variant with strong consistency
In this paper, we modify the proof methods of some previously weakly consistent variants of random forest into strongly consistent proof methods, and...
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Random forest based quantile-oriented sensitivity analysis indices estimation
We propose a random forest based estimation procedure for Quantile-Oriented Sensitivity Analysis—QOSA. In order to be efficient, a cross-validation...
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HFedRF: Horizontal Federated Random Forest
Real-world data is typically dispersed among numerous businesses or governmental agencies, making it difficult to integrate them into data privacy... -
Rapid quantitative analysis of coal composition using laser-induced breakdown spectroscopy coupled with random forest algorithm
Coal is the primary energy source in China, widely used in energy production, industrial processes, and chemical engineering. Due to the complexity...
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Random Forest Algorithm for Forest Fire Prediction
Forest fires threaten the national forestry resources and also endanger the safety of residents. In the past, forest fire research has mostly focused... -
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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FEDSET: Federated Random Forest Based on Differential Privacy
The rapid development of the federated machine learning paradigm has broken down the data barriers in technology between different organizations and... -
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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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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A random forest-based analysis of household survey data to infer insights on digital inequality
This paper examines digital inequalities in Nepal based on a publicly available dataset. We build different random forest classification models and...
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Incremental learning-random forest model-based landslide susceptibility analysis: A case of Ganzhou City, China
Landslide susceptibility mapping (LSM) is a major measure for disaster prevention and control. This paper proposes an incremental learning random...
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Random forest-based multi-faults classification modeling and analysis for intelligent centrifugal pump system
This paper proposes experimental results and a modeling procedure to analyze the factors affecting the defects of centrifugal pumps. The centrifugal...
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Analysis of cloud computing-based education platforms using unsupervised random forest
Cloud computing-based online education has played a vital role in enabling uninterrupted learning during crises such as the COVID-19 pandemic. This...
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Forest fire mapping: a comparison between GIS-based random forest and Bayesian models
In recent decades, fires in natural ecosystems, particularly forests and rangelands, have emerged as a significant threat. To address this challenge,...
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Research on Complaint Sensitivity Analysis Based on Random Forest Algorithm
Complaints are related to the corporate image of power supply enterprises. By predicting complaints and realizing pre-warning of complaints, it is of... -
Random forest, CART, and MLR-based predictive model for unconfined compressive strength of cement reinforced clayey soil: a comparative analysis
This paper discusses the possibility of stabilizing clayey soil with cement and fly ash to strengthen the subgrade pavement layer. This method of...
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Packet Classification Using Improved Random Forest Algorithm
Packet classification in Software-Defined Network (SDN) is a bottleneck process that falls in the critical path of the packet processing in network... -
Random forest-based multipath parameter estimation
Multipath is recognized as one of the major error sources for GNSS urban navigation. This study proposes a random forest (RF)-based multipath...
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Exploring factors influencing urban sprawl and land-use changes analysis using systematic points and random forest classification
This study examines urban sprawl and land-use changes by utilizing systematic points and random forest classification. The research focuses on Neyriz...