GitHub / AtharvKadammm / Calmlytic
An end-to-end machine learning project that predicts anxiety severity using classification models (Naive Bayes, Decision Tree, SVM, Logistic Regression, XGBoost), based on lifestyle, health, and behavioral features.
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PURL: pkg:github/AtharvKadammm/Calmlytic
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Language: Jupyter Notebook
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Created at: about 1 month ago
Updated at: about 1 month ago
Pushed at: about 1 month ago
Last synced at: about 1 month ago
Topics: anxiety-prediction, classification, csv, data-analysis, data-preprocessing-and-cleaning, data-science, data-visualization, ensemble-learning, logistic-regression, machine-learning-algorithms, matplotlib, mental-health, numpy, pandas, python, sci-kit-learn, seaborn, supervised-learning, svm, xgboost