# QFC: A Parallel Software Tool for Feature Construction, Based on Grammatical Evolution
## 4 Experiments
### Experimental Results
The number of generations was varied from 50 to 400, and the average classification error and average regression error for all datasets were measured. The results for this experiment are presented in Table 8. Once again, the dynamics of the proposed method appear as a few generations are enough to achieve high learning rates. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**DATASET** & **RBF** & **MLP** & **FCRBF** & **FCMLP** & **FCNNC** \\ \hline ALCOHOL & 49.19\% & 47.49\% & 35.56\% & 26.57\% & 28.58\% \\ \hline AUSTRALIAN & 34.89\% & 32.21\% & 15.37\% & 14.31\% & 14.24\% \\ \hline BALANCE & 33.42\% & 8.97\% & 14.39\% & 1.42\% & 1.52\% \\ \hline DERMATOLOGY & 62.34\% & 30.58\% & 22.42\% & 15.06\% & 15.42\% \\ \hline GLASS & 50.16\% & 60.25\% & 49.81\% & 55.94\% & 52.62\% \\ \hline HAYES ROTH & 64.36\% & 56.18\% & 34.59\% & 29.58\% & 30.67\% \\ \hline HEART & 31.20\% & 28.34\% & 18.61\% & 15.67\% & 17.21\% \\ \hline HOUSEVOTES & 5.99\% & 6.62\% & 7.15\% & 5.22\% & 3.96\% \\ \hline IONOSPHERE & 16.22\% & 15.14\% & 9.83\% & 9.48\% & 9.92\% \\ \hline LIVERDISORDER & 30.84\% & 31.11\% & 30.77\% & 31.98\% & 30.24\% \\ \hline MAMMOGRAPHIC & 21.38\% & 19.88\% & 16.68\% & 17.92\% & 16.75\% \\ \hline PAGEBLOCKS & 10.09\% & 8.06\% & 9.24\% & 5.58\% & 5.85\% \\ \hline PARKINSONS & 17.41\% & 18.05\% & 8.48\% & 10.82\% & 12.53\% \\ \hline PIMA & 25.75\% & 32.19\% & 24.07\% & 30.02\% & 25.01\% \\ \hline POPFAILURES & 7.04\% & 5.94\% & 4.94\% & 4.94\% & 4.43\% \\ \hline REGIONS2 & 37.49\% & 29.39\% & 25.49\% & 27.52\% & 24.40\% \\ \hline SAHEART & 32.19\% & 34.86\% & 29.10\% & 27.91\% & 27.17\% \\ \hline SEGMENT & 59.69\% & 57.72\% & 39.35\% & 49.52\% & 46.14\% \\ \hline SONAR & 27.85\% & 26.97\% & 24.35\% & 25.38\% & 23.68\% \\ \hline SPIRAL & 44.87\% & 45.77\% & 34.34\% & 45.53\% & 42.69\% \\ \hline TAE & 60.07\% & 56.22\% & 50.95\% & 56.87\% & 55.67\% \\ \hline WDBC & 7.27\% & 8.56\% & 3.39\% & 4.36\% & 4.51\% \\ \hline WINE & 31.41\% & 19.20\% & 7.61\% & 11.08\% & 11.61\% \\ \hline Z\_F\_S & 13.16\% & 10.73\% & 5.48\% & 6.72\% & 6.63\% \\ \hline ZO\_NF\_S & 9.02\% & 8.41\% & 4.08\% & 4.25\% & 4.34\% \\ \hline ZONF\_S & 4.03\% & 2.60\% & 1.89\% & 4.62\% & 3.18\% \\ \hline Z\_O\_N\_F\_S & 48.71\% & 65.45\% & 39.29\% & 40.93\% & 41.19\% \\ \hline ZOO & 21.77\% & 16.67\% & 26.07\% & 13.30\% & 10.33\% \\ \hline AVERAGE & 31.89\% & 28.80\% & 22.11\% & 22.02\% & 21.22\% \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Experimental results between the method and other techniques for the classification datasets. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**DATASET** & **RBF** & **MLP** & **FCRBF** & **FCMLP** & **FCNNC** \\ \hline ABALONE & 7.32 & 7.17 & 4.46 & 4.18 & 4.39 \\ \hline AIRFOIL & 0.05 & 0.003 & 0.002 & 0.001 & 0.001 \\ \hline BASEBALL & 78.89 & 103.60 & 48.04 & 52.50 & 51.40 \\ \hline BK & 0.02 & 0.03 & 0.02 & 0.02 & 0.02 \\ \hline BL & 0.01 & 5.74 & 0.04 & 0.001 & 0.01 \\ \hline CONCRETE & 0.01 & 0.01 & 0.006 & 0.004 & 0.005 \\ \hline DEE & 0.17 & 1.01 & 0.18 & 0.40 & 0.38 \\ \hline DIABETES & 0.49 & 19.86 & 1.49 & 0.58 & 0.61 \\ \hline HOUSING & 57.68 & 43.26 & 12.78 & 28.47 & 17.47 \\ \hline FA & 0.01 & 1.95 & 0.01 & 0.02 & 0.01 \\ \hline MB & 1.91 & 3.39 & 0.48 & 0.12 & 0.06 \\ \hline MORTGAGE & 1.45 & 2.41 & 0.66 & 1.37 & 0.22 \\ \hline NT & 8.15 & 0.05 & 0.25 & 0.007 & 0.02 \\ \hline PY & 0.02 & 105.41 & 0.17 & 0.03 & 0.03 \\ \hline QUAKE & 0.07 & 0.04 & 0.06 & 0.02 & 0.04 \\ \hline TREASURY & 2.02 & 2.93 & 0.29 & 1.41 & 0.11 \\ \hline WANKARA & 0.001 & 0.012 & 0.0004 & 0.0002 & 0.0002 \\ \hline AVERAGE & 9.31 & 17.46 & 4.06 & 5.24 & 4.4 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Experiments for regression datasets.