k-Means Clustering for a sentiment classifier
Simulate a sentiment classifier live in your browser. This runs the real k-Means Clustering solver — adjust the inputs, watch it respond instantly, and export the result. No install, no account.
Controls
Presets
Lloyd's algorithm: assign each point to its nearest centroid, then move each centroid to the mean of its members. Repeat until stable. Try setting k different from the true cluster count.
Data Inspector
Governing equation
Runs locally in your browser — free forever. Scale to the cloud when reality gets heavy.
About this simulation
The full k-Means Clustering tool models a sentiment classifier with the same numerics engineers and scientists use — running entirely client-side. Change any parameter and the result updates in real time, so you can build intuition, check a design, or teach the concept without spreadsheets or installs.
More you can do with k-Means Clustering
Other ways to simulate a sentiment classifier
Frequently asked questions
- How do I simulate a sentiment classifier?
- Open this page and use the live k-Means Clustering tool below — set your inputs and the simulation runs instantly in your browser using real numerics. No install, no account needed.
- Is it free?
- Yes. The simulation runs free in your browser. A one-time unlock or a Pro plan adds advanced parameters, saved presets, data import, and clean exports.
- Can I use my own numbers?
- Absolutely — every input is adjustable, and with data import you can drive a sentiment classifier from your own measurements.