# An Effective Multi-Label Feature Selection Model Towards Eliminating Noisy Features
## 5 Experimental Evaluation
### Example 1: Classification Performance
**} \\ \cline{2-10}  & \multicolumn{1}{c}{**Emotions**} & \multicolumn{1}{c}{**Yeast**} & \multicolumn{1}{c}{**Birds**} & \multicolumn{1}{c}{**Enron**} & \multicolumn{1}{c}{**Genbase**} & \multicolumn{1}{c}{**Business**} & \multicolumn{1}{c}{**Arts**} \\ \hline _MIFS_ & 0.3154 \(\pm\) 0.05 & 0.1767 \(\pm\) 0.01 & 0.2988 \(\pm\) 0.01 & 0.0986 \(\pm\) 0.01 & 0.0586 \(\pm\) 0.03 & 0.0377 \(\pm\) 0.00 & 0.1510 \(\pm\) 0.05 & _0.1624_ \\ _CHFS_ & 0.2404 \(\pm\) 0.02 & 0.1810 \(\pm\) 0.01 & 0.2887 \(\pm\) 0.02 & 0.0959 \(\pm\) 0.00 & 0.0594 \(\pm\) 0.03 & 0.0336 \(\pm\) 0.00 & 0.1341 \(\pm\) 0.00 & _0.1476_ \\ _LISF_ & 0.2711 \(\pm\) 0.02 & 0.1756 \(\pm\) 0.01 & 0.2777 \(\pm\) 0.05 & 0.0962 \(\pm\) 0.01 & 0.0591 \(\pm\) 0.03 & 0.0335 \(\pm\) 0.00 & 0.1341 \(\pm\) 0.00 & _0.1436_ \\ _ELC_ & **0.2379 \(\pm\) 0.02** & **0.1733 \(\pm\) 0.01** & **0.2568 \(\pm\) 0.05** & **0.0924 \(\pm\) 0.00** & **0.0065 \(\pm\) 0.00** & **0.0334 \(\pm\) 0.00** & **0.1332 \(\pm\) 0.00** & **0.1334** \\ \hline \multicolumn{1}{c}{\multirow{2}{*}{**(d)** Ranking loss (the lower the better).}} & \multicolumn{6}{c}{**Education**} & \multicolumn{1}{c}{**Reaction**} & \multicolumn{1}{c}{**Health**} & \multicolumn{1}{c}{**Computers**} & \multicolumn{1}{c}{**Science**} & \multicolumn{1}{c}{**Reference**} & \multicolumn{1}{c}{**Society**} \\ \hline _MIFS_ & 0.0988 \(\pm\) 0.00 & 0.1495 \(\pm\) 0.01 & 0.0498 \(\pm\) 0.00 & 0.0820 \(\pm\) 0.00 & 0.1351 \(\pm\) 0.01 & 0.0849 \(\pm\) 0.00 & 0.1372 \(\pm\) 0.00 & 0.0994 \\ _CMFS_ & 0.0768 \(\pm\) 0.00 & 0.1438 \(\pm\) 0.01 & 0.0492 \(\pm\) 0.00 & 0.0735 \(\pm\) 0.00 & 0.1112 \(\pm\) 0.00 & 0.0734 \(\pm\) 0.00 & 0.1175 \(\pm\) 0.00 & _0.0897_ \\ _LISF_ & 0.0768 \(\pm\) 0.00 & 0.1438 \(\pm\) 0.01 & 0.04 \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline \multicolumn{1}{c}{**Aproaches**} & \multicolumn{6}{c}{**Data Sets**} & \multicolumn{6}{c}{_AVG._} \\ \cline{2-10} \multicolumn{1}{c}{} & **Emotions** & **Yeast** & **Birds** & **Eron** & **Genbase** & **Business** & **Arts** & _AVG._ \\ \hline _MIFS_ & 0.4451 \(\pm\) 0.05 & 0.2403 \(\pm\) 0.01 & 0.7226 \(\pm\) 0.03 & 0.3230 \(\pm\) 0.03 & 0.3698 \(\pm\) 0.21 & 0.1187 \(\pm\) 0.00 & 0.6215 \(\pm\) 0.01 & _0.4059_ \\ _CMFS_ & 0.3871 \(\pm\) 0.02 & 0.2445 \(\pm\) 0.01 & 0.6968 \(\pm\) 0.04 & 0.3093 \(\pm\) 0.02 & 0.3719 \(\pm\) 0.21 & 0.1061 \(\pm\) 0.00 & 0.5518 \(\pm\) 0.01 & _0.3811_ \\ _LSF_ & 0.3986 \(\pm\) 0.03 & 0.2387 \(\pm\) 0.01 & 0.6879 \(\pm\) 0.08 & 0.3158 \(\pm\) 0.05 & 0.3707 \(\pm\) 0.21 & 0.1058 \(\pm\) 0.00 & 0.5509 \(\pm\) 0.01 & _0.3812_ \\ _ELC_ & **0.3664 \(\pm\) 0.03** & **0.2361 \(\pm\) 0.01** & **0.6192 \(\pm\) 0.11** & **0.2988 \(\pm\) 0.01** & **0.0123 \(\pm\) 0.00** & **0.1050 \(\pm\) 0.00** & **0.5464 \(\pm\) 0.00** & **0.3120** \\ \hline \multicolumn{1}{c}{**Education**} & **Reaction** & **Health** & **Computers** & **Science** & **Reference** & **Society** & \\ \hline _MIFS_ & 0.6452 \(\pm\) 0.02 & 0.5292 \(\pm\) 0.02 & 0.3335 \(\pm\) 0.03 & 0.4041 \(\pm\) 0.01 & 0.6761 \(\pm\) 0.02 & 0.4743 \(\pm\) 0.01 & 0.4684 \(\pm\) 0.01 & _0.5104_ \\ _CMFS_ & 0.4899 \(\pm\) 0.01 & 0.5234 \(\pm\) 0.02 & 0.3266 \(\pm\) 0.02 & 0.3738 \(\pm\) 0.01 & 0.5605 \(\pm\) 0.02 & 0.4208 \(\pm\) 0.01 & 0.3933 \(\pm\) 0.01 & _0.4537_ \\ _LSF_ & 0.4993 \(\pm\) 0.01 & 0.5237 \(\pm\) 0.02 & 0.3267 \(\pm\) 0.02 & 0.3735 \(\pm\) 0.00 & 0.5605 \(\pm\) 0.02 & 0.4202 \(\pm\) 0.01 & 0.3937 \(\pm\) 0.01 & _0.4536_ \\ _ELC_ & **0.4923 \(\pm\) 0.00** & **0.5147 \(\pm\) 0.01** & **0.3223 \(\pm\) 0.02** & **0.3699 \(\pm\) 0.00** & **0.5490 \(\pm\) 0.01** & **0.4172 \(\pm\) 0.00** & **0.3885 \(\pm\) 0.00** & **0.4771** \\ \hline \end{tabular}
\end{table} 
Table 2: _Cont._