Logistic Regression Interactive Demo

About Logistic Regression

Logistic Regression is a supervised machine learning algorithm used for classification problems. It predicts the probability that an input belongs to a particular class.

Sigmoid Function: P(Y=1) = 1 / (1 + e^{-(mx + b)})

Interactive Controls

Slope (m): 1

Intercept (b): 0

Input Feature (x): 0

Sigmoid Curve

Classification Interpretation

• If probability > 0.5 → Class 1
• If probability ≤ 0.5 → Class 0

Linear Equation: z = mx + b

Logistic Equation: σ(z) = 1 / (1 + e^-z)

Real-Life Examples of Logistic Regression

• Email Spam Detection
• Customer Churn Prediction
• Loan Default Prediction
• Medical Disease Prediction
• Employee Attrition Analysis