# C-MWCAR: Classification Based on Multiple Weighted Class Association Rules
## 4 C-MWCAR Applied to Hypertension Diagnosis
### Feature Extraction and Discretization
#### 4.2.2 Feature Discretization  
Since all the extracted features are continuous variables and cannot be directly used to mine CARs, we utilize equal-width binning strategy to discretize the feature values into several equal-width intervals. In this study, the value range of each feature is finally discretized into five equal-width intervals based on doctors' advice, which represent \"very low\", \"low\", \"medium\", \"high\", and \"very high\", respectively. The class attribute is inherently discrete and has two categories, i.e., hypertensive patients and normotensive \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Type** & **Features** & **Normotensive** & **Hypertenseive** \\ \hline \multirow{8}{*}{Time domain features} & Max & 1.1704 \(\pm\) 0.1596 & 1.0767 \(\pm\) 0.1804 \\  & Min & 0.6800 \(\pm\) 0.1296 & 0.7206 \(\pm\) 0.1152 \\  & MEAN & 0.8977 \(\pm\) 0.1034 & 0.9010 \(\pm\) 0.1301 \\  & MEDIAN & 0.8860 \(\pm\) 0.1311 & 0.9102 \(\pm\) 0.1405 \\  & SDNN & 0.1034 \(\pm\) 0.0594 & 0.0539 \(\pm\) 0.0401 \\  & RMSSD & 0.1351 \(\pm\) 0.0854 & 0.0698 \(\pm\) 0.0628 \\  & PNN50 & 0.9496 \(\pm\) 0.0331 & 0.8689 \(\pm\) 0.0845 \\ \hline \multirow{4}{*}{Frequency domain features} & vLF & 5.7261 \(\pm\) 4.0433 & 3.6910 \(\pm\) 3.6003 \\  & LF & 3.3063 \(\pm\) 3.2327 & 1.1621 \(\pm\) 1.7799 \\ \cline{1-1}  & HF & 6.0722 \(\pm\) 6.3137 & 1.9928 \(\pm\) 3.7635 \\ \cline{1-1}  & LF/HF & 0.6995 \(\pm\) 0.3277 & 0.9367 \(\pm\) 0.6504 \\ \hline \multirow{4}{*}{Non-linear domain features} & SampEn & 0.63 \(\pm\) 0.14 & 0.6831 \(\pm\) 0.1538 \\ \cline{1-1}  & DFA & 0.7 \(\pm\) 0.2 & 0.65 \(\pm\) 0.23 \\ \cline{1-1}  & SD\({}_{\rm S}\) & 22.99 \(\pm\) 2.56 & 18.67 \(\pm\) 1.76 \\ \cline{1-1} \cline{2-5}  & SD\({}_{\rm L}\) & 51.87 \(\pm\) 6 & 37.39 \(\pm\) 3.42 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Statistical analysis results of the extracted features. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Type** & **Features** & **Definition** & **Description** \\ \hline \multirow{8}{*}{TD 1} & Max & The maximum value of the & To describe the distribution of the heat-beat intervals \\  & Min & The minimum value of the & To describe the distribution of the heat-beat intervals \\  & MEAN & The mean value of the heart-beat intervals & To describe the distribution of the heart-beat intervals \\  & MEDIAN & The median value of the heart-beat intervals & To describe the distribution of the heart-beat intervals \\  & SDNN & The SD 4 of the heart-beat intervals & To measure the overall variation of the heart-beat \\  & RMSSD & The root mean square of the & To reflect the rapid variation of the heart-beat \\  & heart-beat intervals & interval sequence & Interval sequence \\  & PNN50 & The percentage of heart-beat intervals longer than 50 ms & To describe the degree of change in the heart-beat \\ \hline \multirow{4}{*}{FD 2} & vLF & The power in the 0.0033 Hz–0.04 Hz band & To reflect vascular mechanisms caused by \\  & LF & The power in the 0.04 Hz–0.15 Hz band & To reflect sympathetic modulation of heart rate \\  & HF & The power in the 0.15 Hz band & To reflect parasympathetic activity \\  & LF/HF & The ratio of power in the LF and HF bands & To reflect the balance of sympathetic nerve and \\ \hline \multirow{4}{*}{ND 3} & SampEn & The Sample Entropy value with r = 0.15 \(\times\) SD & To investigate the complexity of heart-beat \\  & DFA & The short-term coefficient of detrended & Interval sequence \\  & DFA & fluctuation analysis & heart-beat intervals \\  & SD\({}_{\rm S}\) & The SD of the short-term variability of the & To reflect the short-term variability of the \\  & SD\({}_{\rm L}\) & Poincare plot & heart-beat intervals \\  & SD\({}_{\rm L}\) & The SD of the long-term variability of the & To reflect the long-term variability of the \\  & Poincare plot & heart-beat intervals & \\ \hline \hline \end{tabular}
\end{table} 
Table 3: List of the extracted features. The detailed definitions and descriptions of these features can be found in [20; 28; 29; 30; 31; 32]. subjects.