📐 SVM Interactive Visualizer
Click to add points. Watch SVM find the optimal separating hyperplane with maximum margin!
SVM Concept:
Goal: Find the hyperplane that maximally separates classes
Margin: Distance between hyperplane and nearest points (support vectors)
Support Vectors: Points that lie on the margin boundaries
C Parameter: Trade-off between margin size and classification errors
Kernel Trick: Map data to higher dimension for non-linear separation