Bayes Point Machine toolbox
This toolbox implements the EP algorithms described in my thesis and UAI paper.
bpm.zip
% Bayes Point Machine Toolbox.
% Version 1.1 04-Feb-2005
% Written by Tom Minka (my surname @stat.cmu.edu)
%
% EP
% bpm_task - Define a classification task.
% bpm_ep - Create a bpm_ep object for learning a task.
% train - Train or retrain a bpm_ep object.
% draw - Draw the learned classification boundary.
% get_w - Estimated version space mean (linear kernel only).
% get_v - Estimated version space covariance (linear kernel only).
% get_s - Estimated version space volume (in log domain).
% classify - Classify test data.
% predict - Soft classification of test data.
% bpm_classify - Low-level version of classify.
%
% Utilities
% kernelmtx_linear - Compute matrix of inner products (linear kernel).
% kernelmtx_poly - Compute matrix of inner products (polynomial kernel).
% kernelmtx_rbf - Compute matrix of inner products (RBF kernel).
% kernelmtx_discrete - Compute matrix of inner products (categorical kernel).
% bpm_brute - Compute moments of version space by brute force.
%
% Graphics
% plot_data - Plot classes as x's and o's.
% bpm_draw - Draw a classification boundary.
% show_vs - Render the version space on the sphere.
% draw_vs_point - Plot a labeled point in the version space.
% draw_ellipsoid - Plot an ellipsoid in the version space.
%
% Demos
% test1 - Simple separable test.
% test2 - Nonseparable test.
% test_kernel - Kernel test.
Tom Minka
Last modified: Fri Feb 04 10:32:45 GMT 2005