2D Spatial Decision Boundary
Noisy Sports Regime
Circles
Two Spirals
Moons
Click Mode:
Class A (Purple)
Class B (Green)
Erase
Interactive 2D Space: Click or drag inside the canvas to add or remove ground-truth training samples. Watch decision contours flex during backpropagation.
Model Convergence & Telemetry
Hyperparameters & Regularization
Network Capacity (Hidden Layers)
Learning Rate (η)
0.030
L2 Regularization (λ)
0.0050
Dropout Probability (p)
0.10
Dataset Noise / Variance
0.15
Hidden Activation
Overfitting Trap: Increasing hidden units without regularization allows the model to memorize noisy training points (high variance, zero train loss, huge val loss gap). L2 weight decay smoothly pulls boundaries convex.