Supplementary material

Fuzzy Multi-Instance Classifiers

Experimental results for the paper:

Fuzzy Multi-Instance Classifiers

S. Vluymans, D. Sánchez Tarragó, Y. Saeys, C. Cornelis, F. Herrera
IEEE Transactions on Fuzzy Systems 24(6), p.1395-1409, 2016

Corresponding author: sarah.vluymans@ugent.be

Results

Below, we present the accuracy and kappa values for all methods and all datasets. The datasets are grouped according to application domain: bio-informatics, textual data applications, inductive logic programming and image categorization. We present the mean values per group as well as the overall mean. For each dataset, the row-wise highest value is printed in bold.

These two tables accompany Tables VIII and IX of the paper.

**Accuracy values**
Dataset	BFMIC	IFMIC	MILES	MIWrapper	SimpleMI	MILR	BARTMIP	miSVM	CitationKNN
Musk1	81.522	82.609	88.043	86.957	73.913	85.870	84.783	78.261	86.957
Musk2	72.277	74.257	81.188	82.178	81.188	80.198	86.139	71.287	83.168
Atoms	73.936	73.936	75.000	73.936	67.553	72.872	73.936	66.489	71.277
Bonds	71.809	75.000	82.447	77.660	79.255	72.340	76.064	66.489	74.468
Chains	73.936	73.404	82.447	85.106	78.723	73.404	80.319	66.489	72.872
AntDrugs5	72.000	71.750	72.250	77.250	77.250	74.750	76.250	72.000	72.500
AntDrugs10	80.750	80.750	80.500	80.750	78.500	82.250	81.250	75.500	78.250
AntDrugs20	75.500	75.500	77.000	79.000	76.500	80.250	78.750	69.750	69.250
Mean Bio-IT	75.216	75.901	79.859	80.355	76.610	77.742	79.686	70.783	76.093
TREC1	90.750	92.500	94.500	90.750	94.250	84.750	79.000	88.250	59.250
TREC2	70.250	71.000	80.500	73.750	82.750	69.000	61.000	77.750	46.750
TREC3	77.750	81.000	75.500	84.750	88.500	79.500	63.750	76.750	49.750
TREC4	78.750	82.500	80.500	81.750	87.500	79.250	68.000	79.750	43.750
TREC7	76.000	75.000	78.500	74.000	76.250	72.000	60.500	72.750	44.500
TREC9	67.000	63.750	63.500	61.250	62.250	60.000	57.750	59.750	47.250
TREC10	77.750	75.250	77.500	80.500	75.500	72.250	64.500	72.750	47.000
WIR7	75.221	75.221	56.637	75.221	66.372	75.221	52.212	68.142	61.947
WIR8	77.876	72.566	55.752	71.681	69.027	71.681	53.097	58.407	66.372
WIR9	74.336	72.566	53.097	76.106	73.451	74.336	57.522	61.062	69.027
Mean Text	76.568	76.135	71.599	76.976	77.585	73.799	61.733	71.536	53.560
EastWest	80.000	70.000	75.000	50.000	65.000	65.000	70.000	50.000	50.000
WestEast	80.000	75.000	80.000	50.000	55.000	65.000	55.000	35.000	50.000
Mean LogProg	80.000	72.500	77.500	50.000	60.000	65.000	62.500	42.500	50.000
Elephant	84.500	84.500	78.500	84.500	76.500	79.000	81.500	78.500	50.000
Fox	62.500	59.500	58.500	56.000	63.500	57.000	59.500	50.000	50.000
Tiger	84.000	82.500	77.500	81.000	74.000	77.500	80.000	79.000	50.000
Corel1vs2	92.500	91.000	91.000	91.000	84.500	83.000	92.500	84.500	88.500
Corel1vs3	83.500	83.500	84.500	83.500	87.500	86.500	86.000	82.000	83.000
Corel1vs4	96.500	97.500	96.500	99.000	89.000	88.500	98.500	92.500	98.000
Corel1vs5	98.500	97.000	99.000	92.500	98.500	90.000	99.000	85.000	98.000
Corel2vs3	89.500	88.000	84.000	82.000	74.000	82.000	90.500	69.500	85.000
Corel2vs4	97.000	86.500	94.000	91.000	84.500	89.500	96.000	94.000	91.500
Corel2vs5	98.000	100.000	99.000	91.500	96.000	95.500	100.000	99.000	99.500
Corel3vs4	94.000	88.000	94.000	91.500	90.500	89.500	98.000	58.000	89.500
Corel3vs5	98.500	100.000	99.000	95.000	98.000	84.500	100.000	97.500	98.500
Corel4vs5	100.000	98.500	99.000	93.500	98.000	96.500	100.000	95.500	99.500
Mean Image	90.692	88.962	88.808	87.077	85.731	84.538	90.885	81.923	83.154
Mean	82.013	80.911	80.738	80.139	79.492	78.452	77.616	73.686	70.465

**Kappa values**
Dataset	BFMIC	IFMIC	MILES	MIWrapper	SimpleMI	MILR	BARTMIP	miSVM	CitationKNN
Musk1	0.627	0.650	0.760	0.739	0.478	0.717	0.695	0.564	0.739
Musk2	0.475	0.500	0.601	0.620	0.597	0.586	0.716	0.391	0.643
Atoms	0.408	0.464	0.454	0.351	0.332	0.319	0.403	0.000	0.294
Bonds	0.260	0.462	0.617	0.499	0.567	0.256	0.448	0.000	0.389
Chains	0.334	0.292	0.614	0.671	0.511	0.341	0.531	0.000	0.374
AntDrugs5	0.437	0.432	0.444	0.543	0.545	0.493	0.524	0.437	0.449
AntDrugs10	0.602	0.602	0.605	0.603	0.564	0.635	0.615	0.499	0.556
AntDrugs20	0.493	0.493	0.535	0.572	0.528	0.599	0.568	0.381	0.375
Mean Bio-IT	0.455	0.487	0.579	0.575	0.515	0.493	0.562	0.284	0.477
TREC1	0.815	0.850	0.890	0.815	0.885	0.695	0.580	0.765	0.185
TREC2	0.405	0.420	0.610	0.475	0.655	0.380	0.220	0.555	-0.065
TREC3	0.555	0.620	0.510	0.695	0.770	0.590	0.275	0.535	-0.005
TREC4	0.575	0.650	0.610	0.635	0.750	0.585	0.360	0.595	-0.125
TREC7	0.520	0.500	0.570	0.480	0.525	0.440	0.210	0.455	-0.110
TREC9	0.340	0.275	0.270	0.225	0.245	0.200	0.155	0.195	-0.055
TREC10	0.555	0.505	0.550	0.610	0.510	0.445	0.290	0.455	-0.060
WIR7	0.506	0.508	0.128	0.503	0.328	0.505	0.052	0.368	0.232
WIR8	0.559	0.455	0.114	0.434	0.381	0.435	0.059	0.180	0.326
WIR9	0.488	0.455	0.056	0.522	0.467	0.488	0.152	0.232	0.380
Mean Text	0.532	0.524	0.431	0.539	0.552	0.476	0.235	0.434	0.070
EastWest	0.600	0.400	0.500	0.000	0.300	0.300	0.400	0.000	0.000
WestEast	0.600	0.500	0.600	0.000	0.100	0.300	0.100	-0.300	0.000
Mean LogProg	0.600	0.450	0.550	0.000	0.200	0.300	0.250	-0.150	0.000
Elephant	0.690	0.690	0.570	0.690	0.530	0.580	0.630	0.570	0.000
Fox	0.250	0.190	0.170	0.120	0.270	0.140	0.190	0.000	0.000
Tiger	0.680	0.650	0.550	0.620	0.480	0.550	0.600	0.580	0.000
Corel1vs2	0.850	0.820	0.820	0.820	0.690	0.660	0.850	0.690	0.770
Corel1vs3	0.670	0.670	0.690	0.670	0.750	0.730	0.720	0.640	0.660
Corel1vs4	0.930	0.950	0.930	0.980	0.780	0.770	0.970	0.850	0.960
Corel1vs5	0.970	0.940	0.980	0.850	0.970	0.800	0.980	0.700	0.960
Corel2vs3	0.790	0.760	0.680	0.640	0.480	0.640	0.810	0.390	0.700
Corel2vs4	0.940	0.730	0.880	0.820	0.690	0.790	0.920	0.880	0.830
Corel2vs5	0.960	1.000	0.980	0.830	0.920	0.910	1.000	0.980	0.990
Corel3vs4	0.880	0.760	0.880	0.830	0.810	0.790	0.960	0.160	0.790
Corel3vs5	0.970	1.000	0.980	0.900	0.960	0.690	1.000	0.950	0.970
Corel4vs5	1.000	0.970	0.980	0.870	0.960	0.930	1.000	0.910	0.990
Mean Image	0.814	0.779	0.776	0.742	0.715	0.691	0.818	0.638	0.663
Mean	0.628	0.611	0.610	0.595	0.586	0.554	0.545	0.443	0.398