This toolbox contains re-implementations of four different multi-instance learners, i.e. Diverse Density, Citation-kNN, Iterated-discrim APR, and EM-DD. Ensembles of these single multi-instance learners can be built with this toolbox

MIL-Ensemble
............\Data Preparation
............\................\10-fold cross-validation
............\................\........................\divide_10fold_Musk1.m
............\................\........................\divide_10fold_Musk2.m
............\................\musk data from UCI ML Repository
............\................\................................\clean1.data
............\................\................................\...........\clean1.data
............\................\................................\clean1.data.Z
............\................\................................\clean1.info
............\................\................................\clean1.names
............\................\................................\clean2.data
............\................\................................\...........\clean2.data
............\................\................................\clean2.data.Z
............\................\................................\clean2.info
............\................\................................\clean2.names
............\................\................................\Index
............\................\Preprocessed data
............\................\.................\Musk1
............\................\.................\.....\all.txt
............\................\.................\.....\molecule_num.TXT
............\................\.................\Musk2
............\................\.................\.....\all.txt
............\................\.................\.....\molecule_num.TXT
............\Ensemble Algorithm
............\..................\APR
............\..................\...\Bagging_APR_Musk1.m
............\..................\...\Bagging_APR_Musk2.m
............\..................\auxiliary function
............\..................\..................\copy.m
............\..................\C-kNN
............\..................\.....\Bagging_C_kNN_Musk1.m
............\..................\.....\Bagging_C_kNN_Musk2.m
............\..................\Diverse Density
............\..................\...............\Bagging_DD_Musk1.m
............\..................\...............\Bagging_DD_Musk2.m
............\..................\EM-DD
............\..................\.....\Bagging_EMDD_Musk1.m
............\..................\.....\Bagging_EMDD_Musk2.m
............\Individual Algorithm
............\....................\Citation KNN
............\....................\............\CKNN.m
............\....................\............\minHausdorff.m
............\....................\Diverse Density
............\....................\...............\dfpmin.m
............\....................\...............\DInstance.m
............\....................\...............\DNBag.m
............\....................\...............\DPBag.m
............\....................\...............\D_neg_log_DD.m
............\....................\...............\lnsrch.m
............\....................\...............\maxDD.m
............\....................\...............\neg_log_DD.m
............\....................\...............\PInstance.m
............\....................\...............\PNBag.m
............\....................\...............\PPBag.m
............\....................\EM-DD
............\....................\.....\EMDD.m
............\....................\.....\NLDD.m
............\....................\IDAPR
............\....................\.....\Discrim.m
............\....................\.....\Expand.m
............\....................\.....\Grow.m
............\....................\.....\IDAPR.m
............\readme.txt

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