Visualisation of Machine Learning Algorithms

by maurits on 5/30/2011, 12:53 PM with 11 comments
  • by vedantk on 5/30/2011, 2:40 PM

    The install.sh and install_script.sh scripts are Mac-dependent. How would you compile this on Linux? Qmake?

    edit: Yep. Clone the git repo, then run qmake, followed by make.

    edit #2: Here is a patch I wrote to make the project compile under OpenCV 2.2, and Linux: https://gist.github.com/999061

  • by vinyl on 5/30/2011, 1:37 PM

    Wow. This could prove an invaluable tool for teaching. Great UI (love the way you can build the dataset with a paintbrush), top-quality visualization, wide choice of algorithms... Much better than R scripts if you want to show basic algorithms at work to a bunch of students. Many thanks

  • by Emore on 5/30/2011, 9:38 PM

    Here's another one, a simple Applet that lets you apply various classification algorithms on 2D data: http://www.cs.technion.ac.il/~rani/LocBoost/

  • by jwr on 5/31/2011, 11:03 AM

    Thank you! This is very, very useful. Not only to beginners, but also to those of us who want to roughly compare the behavior of several algorithms. You can estimate things like sensitivity to parameters and quickly visualize exactly how they behave.

    It's a very useful tool.

  • by maeon3 on 5/30/2011, 2:18 PM

    Patch through a black and white video into this tool and watch how the algorithm tries to find patterns in a 2d reprsentation of a 3d space. Maybe it can predict where the table ends without full view of the table.

    Neat stuff, it is the beginning of machine notion of object permanence. Filling in the gaps and making educated guesses about what kind of function controls where a sequence originated from.