Do I need to install anything?

No. It runs in any modern browser, free, with no account required.

For First Responders · SVM Maximum Margin

SVM Maximum Margin for a sentiment classifier

Built for first responders planning or training for real incidents. Run fast what-if scenarios for response planning and training — no software to install in the field. Simulate a sentiment classifier live below — adjust the inputs and watch it respond, right in your browser.

SVM Maximum MarginLive

the widest possible street

Controls

Presets

Boundary angle (°)

Boundary offset

A support vector machine picks the separating line with the widest margin to the nearest points of each class — the support vectors. A fatter margin generalizes better to new data. Try to hand-tune the line to maximize the dashed gap. Educational tool.

▶ Run in Python

Data Inspector

Margin width0.000

Separates classes?no — misclassified

Governing equation

w, b min \frac{1}{2} ∥ w ∥^{2} s.t. y_{i} (w \cdot x_{i} + b) \geq 1, margin = \frac{2}{∥ w ∥} = 0.000

Reading this result: This orientation misclassifies at least one point, so the margin is meaningless until the two classes are cleanly separated first.

Runs locally in your browser — free forever. Scale to the cloud when reality gets heavy.

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Frequently asked questions

Is this good for first responders?: Yes — this version of "SVM Maximum Margin for a sentiment classifier" is framed for first responders planning or training for real incidents. Run fast what-if scenarios for response planning and training — no software to install in the field.
Do I need to install anything?: No. It runs in any modern browser, free, with no account required.