Support Vectors: The Few Tiles That Hold the Line
This lesson is part of the course
In this lesson
You find the tiles that sit on the edge of the street, rebuild the weights from the given α values as Σ α·y·x and the bias from the support vectors alone, and see why all other tiles could be removed without moving the line.
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Lessons in this course
- A Separating Line: Scores, Signs and Predicted Classes Locked
- Margins: Functional Margin, Geometric Margin and the Width of the Street Locked
- Hinge Loss: Points Outside, Inside and on the Wrong Side of the Margin Locked
- Soft Margins and C: Trading a Wide Street Against Hinge Loss Locked
- Training by Sub-Gradient Steps: Update Rules, a Fixed Learning Rate and the Objective per Epoch Locked
- Support Vectors: The Few Tiles That Hold the Line Locked
- Kernels: Feature Maps for a Ring-Shaped Set, Polynomial and Radial Kernel Tables Locked
- Capstone: Kernel Decisions Σ α·y·K + b and Several Classes with One-vs-Rest Locked