WEEK 07

PROGRESS: 5 / 11

MODELING // LOGISTIC REGRESSION [ACTIVE SESSION]

SUMMARY // WHAT WE LEARNED

📈 Logistic Regression: Used for classification tasks, predicting categories instead of continuous values.
🔄 The Sigmoid Function: Squashing outputs into probabilities between 0 and 1.
🎯 Evaluation Metrics: Accuracy, Precision, Recall, F1-Score, and the Confusion Matrix.
⚖️ Decision Boundaries: Setting thresholds (like 0.5) to classify a data point into Class 0 or Class 1.
🫀 Framingham Heart Study: Predicting the 10-year risk of coronary heart disease using patient data.

CORE MATERIALS