Download the .tgz bundle of MATLAB code
- MATLAB Lightspeed toolbox
|BICfn.m||Calculating the Bayesian Information Criteria.|
|Bin_Class_EM_fn4.m||Implements the EM algorithm for Bayesian classification with averaged feature clusters.|
|Bin_Class_EM_loop.m||Runs Bin_Class_EM_fn4.m multiple times and stores the results.|
|Bin_Exps_Loop.sh||An example shell script for submission to a grid system.|
|GammaUpdate3.m||Update to γ in the E-step of the EM algorithm.|
|LogJoint3.m||Calculating the log joint likelihood.|
|PiUpdate.m||Update to π in the M-step of the EM algorithm.|
|SigmaSqdUpdate3.m||Update to σ in the M-step of the EM algorithm.|
|ThetaUpdate.m||Update to θ in the M-step of the EM algorithm.|
|wUpdate.m||Update to w in the M-step of the EM algorithm.|
|yUpdate.m||Update to y in the E-step of the EM algorithm.|
- Prepare your data appropriately (as described in );
- Download .tgz bundle;
- Set the values of lightspeed_dir, working_dir, data_file, dataset_string in Bin_Class_EM_loop.m to correspond to your file structure.
- Set the value of data_file in Bin_Class_EM_fn4.m to match the value in Bin_Class_EM_loop.m.
- If distributing across a cluster, use Bin_Exps_Loop.sh as a template, making sure you refer to the correct version of MATLAB (i.e., give the full path to the executable).