The package includes the MATLAB code of algorithms MIMLBOOST and MIMLSVM, both which are designed to deal with multi-instance multi-label learning. It is in particular useful when a real-world object is associated with multiple instances as well as multiple labels simultaneously. A Readme file and some sample files are included in the package.

MIMLBoost&MIMLSVM\auxiliary\Average_precision.m
MIMLBoost&MIMLSVM\auxiliary\coverage.m
MIMLBoost&MIMLSVM\auxiliary\Hamming_loss.m
MIMLBoost&MIMLSVM\auxiliary\maxHausdorff.m
MIMLBoost&MIMLSVM\auxiliary\min_max_norm.m
MIMLBoost&MIMLSVM\auxiliary\normalize_bags.m
MIMLBoost&MIMLSVM\auxiliary\One_error.m
MIMLBoost&MIMLSVM\auxiliary\Ranking_loss.m
MIMLBoost&MIMLSVM\libsvm-mat-2.86-1.zip
MIMLBoost&MIMLSVM\MIMLBoost\MIMLBoost_test.m
MIMLBoost&MIMLSVM\MIMLBoost\MIMLBoost_train.m
MIMLBoost&MIMLSVM\MIMLBoost\MIML_error.m
MIMLBoost&MIMLSVM\MIMLSVM\MIMLSVM.m
MIMLBoost&MIMLSVM\MIMLSVM\MIML_cluster.m
MIMLBoost&MIMLSVM\readme.txt
MIMLBoost&MIMLSVM\sample\10CV.mat
MIMLBoost&MIMLSVM\sample\sample.m
MIMLBoost&MIMLSVM\auxiliary
MIMLBoost&MIMLSVM\MIMLBoost
MIMLBoost&MIMLSVM\MIMLSVM
MIMLBoost&MIMLSVM\sample
MIMLBoost&MIMLSVM

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