This is a 3D visualization of how the Expectation Maximization algorithm learns a Gaussian Mixture Model for 3-dimensional data.
--How it works--
The data is either read in or generated in general-covariance gaussian clusters. For each value of k (number of Gaussians to fit), a movie is played showing the evolution of the GMM through the iterations of the EM algorithm. The true model is only available at each iteration (viewed...
Alternate checkerboard visualization of 2 RGB images
out=checkvis(im1, im2, sqsize)
im1, im2 ... RGB source images, MUST have same size!
sqsize ... square side size (optional agument, default is 32pixels)
This is the data set you will need to participate in the Data Visualization contest. For more information, refer to the rules posted here.
You can also follow the latest...
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