# Sample-Pair Envelope Diamond Autoencoder Ensemble Algorithm for Chronic Disease Recognition
## 4 Experimental Results and Analysis
### Algorithm Comparison
#### 4.4.1 Comparison with Typical Feature Learning Algorithms
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Dataset** & \begin{tabular}{c} **Performance** \\ **Indices** \\ \end{tabular} & \begin{tabular}{c} **OFs** \\ **(\%)** \\ \end{tabular} & **PCA (\%)** & **LDA (\%)** & **LPP (\%)** & **Relief (\%)** & \
\begin{tabular}{c} **LASSO** \\ **(\%)** \\ \end{tabular} &
\begin{tabular}{c} **SP_DFsaeLA** \\ **(Proposed) (\%)** \\ \end{tabular} \\ \hline \multirow{4}{*}{PID} & Acc & 79.29 & 80.03 & 80.21 & 80.03 & 78.17 & 77.59 & **84.54** \\  & Prec & 79.30 & 79.82 & 80.09 & 79.38 & 78.30 & 77.76 & **88.50** \\  & Sens & 79.48 & 80.59 & 80.58 & 81.33 & 78.34 & 77.59 & **80.99** \\  & Spec & 79.11 & 79.48 & 79.85 & 78.74 & 77.99 & 77.60 & **88.11** \\  & F1\_score & 79.32 & 80.13 & 80.30 & 80.25 & 78.24 & 77.67 & **84.18** \\ \hline \multirow{4}{*}{Maxlettle} & Acc & 81.24 & 91.73 & 97.00 & 95.84 & 90.62 & 84.52 & **97.89** \\  & Prec & 84.37 & 91.33 & 94.85 & 96.37 & 88.32 & 91.86 & **100** \\  & Sens & 79.33 & 93.78 & 100 & 95.78 & 93.78 & 77.33 & **95.56** \\  & Spec & 83.33 & 89.78 & 94.00 & 96.00 & 87.56 & 91.78 & **100** \\  & F1\_score & 81.02 & 91.91 & 97.23 & 95.87 & 90.92 & 82.65 & **97.50** \\ \hline \multirow{4}{*}{Heart} & Acc & 91.67 & 95.42 & 94.17 & 94.58 & 93.33 & 88.75 & **96.67** \\  & Prec & 94.19 & 95.93 & 95.12 & 94.36 & 94.85 & 89.54 & **97.59** \\  & Sens & 89.17 & 95.00 & 93.33 & 95.00 & 91.67 & 88.33 & **95.83** \\  & Spec & 94.17 & 95.83 & 95.00 & 94.17 & 95.00 & 89.17 & **97.50** \\  & F1\_score & 91.54 & 95.39 & 94.12 & 94.61 & 93.19 & 88.76 & **96.65** \\ \hline \multirow{4}{*}{WDBC} & Acc & 99.06 & 99.29 & 99.29 & 99.29 & 99.29 & 98.11 & **99.53** \\  & Prec & 100 & 100 & 100 & 100 & 99.53 & 99.05 & **100** \\  & Sens & 98.11 & 98.58 & 98.58 & 98.57 & 99.05 & 97.17 & **99.53** \\  & Spec & 100 & 100 & 100 & 100 & 99.52 & 99.06 & **100** \\  & F1\_score & 99.04 & 99.28 & 99.28 & 99.27 & 99.28 & 98.09 & **99.53** \\ \hline \multirow{4}{*}{PD} & Acc & 68.94 & 71.25 & 69.90 & 70.58 & 71.25 & 67.21 & **79.93** \\  & Prec & 69.84 & 71.89 & 70.80 & 71.35 & 71.72 & 66.67 & **80.05** \\  & Sens & 67.31 & 70.19 & 68.27 & 69.42 & 70.38 & 68.65 & **79.81** \\  & Spec & 70.58 & 72.31 & 71.54 & 71.73 & 72.12 & 65.77 & **80.05** \\  & F1\_score & 68.29 & 70.88 & 69.26 & 70.12 & 70.86 & 67.49 & **79.60** \\ \hline \multirow{4}{*}{AD} & Acc & 58.89 & 71.11 & 72.22 & 66.67 & 68.89 & 62.22 & **72.22** \\  & Prec & 65.78 & 74.01 & **80.00** & 66.83 & 73.70 & 66.30 & 74.54 \\  & Sens & 58.89 & 71.11 & 72.22 & 66.67 & 68.89 & 62.22 & **72.22** \\  & Spec & 79.44 & 85.56 & 86.11 & 83.33 & 84.44 & 81.11 & **86.11** \\  & F1\_score & 62.07 & 72.00 & **75.91** & 66.75 & 71.19 & 64.07 & 73.36 \\ \hline \multirow{4}{*}{Vehicle} & Acc & 84.65 & 87.55 & 87.15 & 87.44 & 86.79 & 82.77 & **87.80** \\  & Prec & 84.76 & 87.61 & 87.56 & 87.46 & 87.20 & 83.20 & **88.73** \\  & Sens & 84.65 & 87.55 & 87.17 & 87.44 & 86.78 & 82.77 & **87.82** \\  & Spec & 94.89 & 95.86 & 95.05 & 95.14 & 95.60 & 94.25 & **95.93** \\  & F1\_score & 84.71 & 87.58 & 87.36 & 87.45 & 86.99 & 82.99 & **88.27** \\ \hline \multirow{4}{*}{Wisconsin} & Acc & 97.70 & 98.53 & 98.54 & 98.54 & 98.11 & 97.70 & **99.37** \\  & Prec & 98.31 & 97.55 & 98.34 & 97.94 & 97.58 & 97.52 & **98.77** \\  & Sens & 97.06 & 99.57 & 98.74 & 99.16 & 98.74 & 97.91 & **100** \\  & Spec & 98.32 & 97.49 & 98.32 & 97.91 & 97.49 & 97.49 & **98.74** \\  & F1\_score & 97.67 & 98.55 & 98.53 & 98.54 & 98.13 & 97.70 & **99.38** \\ \hline \multirow{4}{*}{lung} & Acc & 91.75 & 91.75 & 94.28 & 84.65 & 91.42 & 88.57 & **95.24** \\  & Prec & 87.78 & 87.78 & **94.44** & 84.76 & 92.22 & 90.00 & 91.67 \\ \cline{1-1}  & Sens & 91.11 & 91.11 & 96.11 & 84.65 & 92.22 & 90.00 & **96.67** \\ \cline{1-1}  & Spec & 93.67 & 93.67 & **97.00** & 94.89 & 95.67 & 94.33 & 95.83 \\ \cline{1-1}  & F1\_score & 89.33 & 89.33 & **95.24** & 84.71 & 92.22 & 90.00 & 93.84 \\ \hline \hline \end{tabular}
\end{table} 
Table 12: Comparison of typical feature learning algorithms.