Applet Demonstration

A Java applet demonstrating the piecewise linear classification algorithm of Tenmoto et al.[1] should appear below. If it does not, Java is most likely disabled in your browser. Despite the platform independence of Java, this applet is known to be buggy on some versions on Linux. Details on the interesting points of the algorithm implementation can be found here.

How It Works

The applet is designed to show the construction of the hyperplanes used to create piecewise linear classifier. Enter some prototype points from several different classes by clicking on the left window with your mouse. Pressing "Links" adds random data points associated with each prototype, and identifies the Tomek links. Pressing "Next Hyperplane" identifies the next hyperplane. The left window displays each hyperplane individually along with the Tomek links it cuts. This is enough to get you started, for a more detailed description of the settings click here.


Max Local Error: Use the scroll bar to set the maximum acceptable classification error rate when constructing hyperplanes. This ranges from 0.0 to 0.5. A higher acceptable error results in more hyperplanes required for classification. A lower acceptable error results in fewer hyperplanes required for classification.

Points Per Prototype: Use the scroll bar to set the number of random points assigned to each prototype. Warning: the more points, the slower the identification of the hyperplanes!

This web page prepared by
Matt Toews (
as a term project for the course
Computer Science 644 - Pattern Recognition
at the
McGill Center for Intelligent Machines