Binary Classification Demo
This visualizer shows a simple classifier for cat videos using two hand-crafted features: "has whiskers" and "cat eyes".
You can edit the data points and see how a linear classifier separates cat and not-cat videos.
| Has Whiskers | Cat Eyes | Label (Cat?) |
|---|---|---|
Cat
✖
How Linear Classification Works
1. Each data point has two features: whiskers (0-1) and cat eyes (0-1)
2. The classifier learns a decision boundary (line) to separate cats from non-cats
3. Points above the line are classified as cats, below as non-cats
4. The algorithm adjusts the line to minimize classification errors
