Interactive Logistic Regression Demo - Simple

Adjust parameters and visualize logistic regression predictions in real-time.

Dataset Size: 25 Learning Rate: Iterations:

Logistic Regression Model

Model Formula:

ŷ = sigmoid(XW + b)

Where sigmoid(z) = 1 / (1 + e^-z)

Trained Parameters:

Weight (W):

Bias (b):

Error:

1. Input Matrix (X):

2. Weight Vector (W, b):

3. Compute Z = XW + b:

4. Apply Sigmoid to Z to get Predictions (ŷ):