As exploration for new resources increasingly relies upon deeper and deeper drilling to investigate through overburden, exploration projects will encounter significantly higher drilling costs to ...
The classification models built on class imbalanced data sets tend to prioritize the accuracy of the majority class, and thus, the minority class generally has a higher misclassification rate.
In this study, multi-source remote sensing data and machine learning algorithms were used to delineate the prospect area of remote sensing geological prospecting in eastern Botswana. Landsat 8 remote ...
The operation of the power grid is closely related to meteorological disasters. Changes in meteorological conditions may have an impact on the operation and stability of the power system, leading to ...
# Description: A machine learning model using Random Forest to predict customer purchases on an e-commerce platform. # 1. Identify key predictors of customer purchases. # 2. Assess the accuracy and ...
Planning Department, Usutu Forest, Bhunya, Eswatini. Figure 1. Study site Map. (A): Locality of Eswatini within the Southern African region. (B): Locality of the Usuthu Forest Plantations within ...
Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the random forest regression technique (and a variant called bagging regression), where the goal is to ...
Abstract: Mangroves are in coastal zones where mass-energy exchange is most active. Their functions in high productivity, strong carbon sequestration capacity, and rich ecosystem services are crucial ...
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