# Probability Analysis of Hypertension-Related Symptoms Based on XGBoost and Clustering Algorithm
## 3 Experiment and Result Discussion
\begin{table}
\begin{tabular}{c c c c c c} \hline
**Variable** & **Component** & **Cumulative** & **Variable** & **Component** & **Cumulative** \\
**Number** & **Contribution** & **Contribution** & **Number** & **Contribution** & **Contribution** \\ \hline
1 & 0.57 & 0.57 & 12 & 0.01 & 0.98 \\
2 & 0.18 & 0.75 & 13 & 0.00 & 0.99 \\
3 & 0.05 & 0.80 & 14 & 0.00 & 0.99 \\
4 & 0.05 & 0.85 & 15 & 0.00 & 0.99 \\
5 & 0.04 & 0.89 & 16 & 0.00 & 0.99 \\
6 & 0.03 & 0.92 & 17 & 0.00 & 1.00 \\
7 & 0.02 & 0.94 & 18 & 0.00 & 1.00 \\
8 & 0.01 & 0.95 & 19 & 0.00 & 1.00 \\
9 & 0.01 & 0.96 & 20 & 0.00 & 1.00 \\
10 & 0.01 & 0.97 & 21 & 0.00 & 1.00 \\
11 & 0.01 & 0.98 & 22 & 0.00 & 1.00 \\ \hline \end{tabular}
\end{table} 
Table 2: Contribution table. Figure 3A shows the clustering results. The red and green points in the graph represent the clustering centers of two types. This graph shows the relationship between the density and distance of each point. The clustering centers usually fall on the right side of the graph. Two black-colored points in Figure 3B. represent two clustering centers, and it is obvious that the \(\gamma\) values of these two points are large, so they will be given priority when considering clustering centers. After the center point is determined, points other than the two center points must select a class based on the conditions of the cluster. The final clustering results are shown in Table 4. The total sample size is 531. The number of patients in the first category is 138, and the center point is the patient numbered 217. In a class, the average density is calculated, the point where the density exceeds the average density is at the core position, and the point where the density is lower than the average density is due to the position of the halo. According to the density of the sample points, 13 people are in the core position of the first category, and 125 people are in the halo position. The number of patients in the second category is 393, and the center point is the number 355. Similarly, according to the density of the sample points, 64 people are in the core position of the second category, and 329 people are in the halo position. A represents ventricular hypertrophy, B represents vascular sclerosis, C represents lower limb ischemia, D represents renal insufficiency, E represents microalbuminuria, F represents fundus disease, G represents stroke. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Category** & **Core** & **Halo** & **Total** & **Center** \\ \hline
1 & 13 & 125 & 138 & 217 \\
2 & 64 & 329 & 393 & 355 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Clustering result. Figure 3: Clustering diagram. (**A**) The \(\rho\) and \(\delta\) values of each point; (**B**) The \(\gamma\) values of each  
Table 5 describes an analysis of the related symptoms of different types of hypertension after classification. There are two types of hypertension, the number of one group of patients was 138, and the number of two groups of patients was 393. The table shows the number of patients with different types of hypertension corresponding to different symptoms, and the corresponding proportion of each type of symptoms, the appearance of different symptoms means that there is damage to the corresponding target organ, such as ventricular hypertrophy, and shows that hypertension caused damage to the heart of patients and that renal insufficiency means that hypertension caused damage to the kidneys of patients. For heart target organs, only about 10% of the patients in the first group developed ventricular hypertrophy, while 34.9% of the patients in the second group developed ventricular hypertrophy. For vascular sclerosis, both the first group and the second group had a very high proportion of the symptoms; the first group was close to 90% of the patients, the second group of patients is as high as 96.4% of the proportion, which means patients with hypertension will generally appear in the symptoms of vascular sclerosis.