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Is your feature request related to a problem? Please describe.
Space environment modeling requires accurate prediction of electron energy flux to assess and mitigate space weather impacts on satellite operations. The primary problem addressed here is to predict ELE_TOTAL_ENERGY_FLUX using environmental and telemetry features, providing a reliable estimate of electron flux to improve satellite resilience in varying space weather conditions. The challenge is to identify a robust model that minimizes prediction error, offering precise flux predictions based on environmental indicators.
Describe the solution you'd like
The "Hepatitis Prediction Model" is a machine learning application designed to predict hepatitis presence based on various patient health metrics. Using a Random Forest classifier, this model identifies patterns in historical patient data to classify whether a patient is at risk of hepatitis or not. The model aims to assist healthcare providers by offering a tool to help in early detection of hepatitis, potentially improving patient outcomes through timely intervention.