Predicted marijuana use behavior among youth using decision trees and ensemble methods. Achieved over 89% accuracy and identified peer influence and friend opinions as key factors.
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Updated
Apr 16, 2025 - HTML
Predicted marijuana use behavior among youth using decision trees and ensemble methods. Achieved over 89% accuracy and identified peer influence and friend opinions as key factors.
💧Water Potability Prediction .🔬 AI-Powered Analysis: Predicts water safety using machine learning. 📊 Key Metrics: Evaluates pH, sulfate, and other attributes. 🌐Interactive Interface: Flask-based with Home, Blog, and Prediction Form. ✅ Accurate Results: Ensures reliable insights for water safety.
This project explains why and how are the Bagged Models better than the Complete Model. Bagged Model parameters have tighter confidence interval and a lower bias.
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