This webpage provides an interactive demo of the K-Means clustering algorithm for two dimensional numerical data.

1) Enter the input data in the textbox below, where each line is a data point defined by two numbers separated by a space. Numbers must be in the [0,10] interval.

Or generate 100 random points:

2) Choose the value of k:

3) For visualization purpose, you may adjust the size of data points:

4) Click run to execute K-Means:

**Result**:

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Want to try a fast implementation of K-Means in Java ? Check the open-source SPMF data mining software

Return to the list of online tools

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© Philippe Fournier-Viger, 2023