The development and implementation of an earthquake magnitude classification AI model can help our collective preparedness, response capabilities, and overall resilience in the face of seismic events. It can aid in public safety, risk mitigation, and informed decision-making across various sectors to lead to a safer society.
This is a earthquake magnitude classification AI model using machine learning techniques. The model is built using a dataset containing features such as latitude, longitude, depth, and others, with earthquake magnitudes as the target variable. The steps include data preprocessing, which involves handling missing values, encoding categorical variables, and splitting the data into training and testing sets. A Random Forest Classifier is utilized for model training, and predictions are made on the test set. The model's performance is evaluated using metrics such as a confusion matrix and a classification report.