# A Feature Selection Method for Multi-Label Text Based on Feature Importance
## 4 Experiment and Results
### Experimental Results and Analysis
#### 4.4.1 Proposed Algorithm Validation Experiment
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Data Set** & **Algorithm** & \(t\) & **AP(\%)\(\uparrow\)** & **HL(\%)\(\downarrow\)** & **OE(\%)\(\downarrow\)** & **CV(\%)\(\downarrow\)** & \(RL(\%)\(\downarrow\)\(\downarrow\)** \\ \hline \multirow{3}{*}{Medical} & BRKNN & 10\% & 23.92 & 22.77 & 40.81 & 49.16 & 53.21 \\ \cline{2-8}  & MLKNN & 10\% & 11.91 & 19.82 & 29.39 & 27.52 & 30.10 \\ \hline \multirow{3}{*}{Business} & BRKNN & 40\% & 2.69 & 8.63 & 18.82 & 29.29 & 30.20 \\ \cline{2-8}  & MLKNN & 40\% & 1.65 & 7.14 & 12.49 & 12.29 & 18.91 \\ \hline \multirow{3}{*}{Computers} & BRKNN & 20\% & 6.88 & 12.99 & 9.33 & -3.59* & -1.07* \\ \cline{2-8}  & MLKNN & 20\% & 5.88 & 11.59 & 8.07 & 14.17 & 16.42 \\ \hline \multirow{3}{*}{Entertainment} & BRKNN & 20\% & 36.39 & 31.88 & 28.82 & 25.56 & 31.58 \\ \cline{2-8}  & MLKNN & 20\% & 16.09 & 12.67 & 23.39 & 14.88 & 18.25 \\ \hline \multirow{3}{*}{Health} & BRKNN & 20\% & 67.79 & 54.09 & 44.32 & 38.30 & 43.77 \\ \cline{2-8}  & MLKNN & 30\% & 9.96 & 22.47 & 20.99 & 15.38 & 21.59 \\ \hline \multirow{3}{*}{Social} & BRKNN & 10\% & 7.74 & 16.48 & 19.76 & 7.03 & 10.98 \\ \cline{2-8}  & MLKNN & 10\% & 6.61 & 12.89 & 16.56 & 15.62 & 18.35 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Increase (decrease) percentage of each evaluation metrics on six data sets. Figure 7: Experimental results on Social data set. **(a)** Average Precision; **(b)** Hamming Loss; (c) One Error; **(d)** Coverage; **(e)** Ranking Loss. dimensions, respectively; and Average denotes the average of the classification results in five different dimensions. \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Algorithm** & **Evaluation** & **BaseLine** & **10\%** & **20\%** & **30\%** & **40\%** & **50\%** & **Average** \\ \hline \multirow{4}{*}{ALA} & AP & 0.8500 & 0.8482 & 0.8611 & 0.8692 & 0.8729 & 0.8696 & 0.8642 \\ \cline{2-8}  & HL & 0.0278 & 0.0287 & 0.0268 & 0.0255 & 0.0254 & 0.0260 & 0.0265 \\ \cline{2-8}  & OE & 0.1233 & 0.1298 & 0.1156 & 0.1055 & 0.1001 & 0.1073 & 0.1117 \\ \cline{2-8}  & CV & 4.8337 & 4.1161 & 3.9341 & 3.6375 & 3.4179 & 3.6064 & 3.7424 \\ \cline{2-8}  & RL & 0.0831 & 0.0756 & 0.0696 & 0.0627 & 0.0580 & 0.0632 & 0.0658 \\ \hline \multirow{4}{*}{NLA} & AP & 0.8617 & 0.8668 & 0.8713 & 0.8696 & 0.8684 & 0.8662 & 0.8685 \\ \cline{2-8}  & HL & 0.0413 & 0.0259 & 0.0252 & 0.0310 & 0.0353 & 0.0378 & 0.0310 \\ \cline{2-8}  & OE & 0.1323 & 0.1328 & 0.1277 & 0.1279 & 0.1271 & 0.1283 & 0.1288 \\ \cline{2-8}  & CV & 2.6461 & 2.5978 & 2.5058 & 2.5241 & 2.5443 & 2.5792 & 2.5502 \\ \cline{2-8}  & RL & 0.0510 & 0.0492 & 0.0462 & 0.0468 & 0.0475 & 0.0487 & 0.0477 \\ \hline \multirow{4}{*}{LLA} & AP & 0.8459 & 0.8518 & 0.8626 & 0.8685 & 0.8644 & 0.8585 & 0.8612 \\ \cline{2-8}  & HL & 0.0283 & 0.0289 & 0.0269 & 0.0260 & 0.0260 & 0.0267 & 0.0269 \\ \cline{2-8}  & OE & 0.1286 & 0.1315 & 0.1177 & 0.1104 & 0.1083 & 0.1144 & 0.1165 \\ \cline{2-8}  & CV & 4.9435 & 3.9726 & 3.8237 & 3.4919 & 4.0517 & 4.2886 & 3.9257 \\ \cline{2-8}  & \(RL\) & 0.0853 & 0.0731 & 0.0672 & 0.0596 & 0.0691 & 0.0734 & 0.0685 \\ \hline \multirow{4}{*}{NLA} & AP & 0.8459 & 0.8460 & 0.8648 & 0.8697 & 0.8687 & 0.8650 & 0.8628 \\ \cline{2-8}  & HL & 0.0283 & 0.0287 & 0.0267 & 0.0256 & 0.0260 & 0.0266 & 0.0267 \\ \cline{2-8}  & OE & 0.1286 & 0.1305 & 0.1141 & 0.1077 & 0.1071 & 0.1128 & 0.1144 \\ \cline{2-8}  & CV & 4.9435 & 4.2223 & 3.7887 & 3.5617 & 3.4172 & 3.6875 & 3.7355 \\ \cline{2-8}  & RL & 0.0853 & 0.0784 & 0.0664 & 0.0612 & 0.0587 & 0.0651 & 0.0660 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Experimental results on Business data set.