## 4 Materials and Methods
### Data Description and Analysis  
The distribution of rockburst categories is shown in Figure 1 with no rockbursts (only 53 cases), strong intense rockbursts (56 cases), light rockbursts (101 cases), and moderate rockbursts (120 cases). In this study, the influence factors in the dataset are maximum tangential stress (\(\sigma_{0}\)), uniaxial compressive strength (\(\sigma_{c}\)), tensile strength (\(\sigma_{t}\)), elastic strain energy index (\(W_{\rm{et}}\)), stress concentration factor (SCF), rock brittleness index B1 (B1 = \(\sigma_{c}/\sigma_{t}\)), rock brittleness index B2 (B2 = \(\left(\sigma_{c}-\sigma_{t}\right)/(\sigma_{c}+\sigma_{t})\)), and seven others.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**References**} & \multirow{2}{*}{**Number of Cases**} & \multicolumn{6}{c}{**Rockburst Label**} \\ \cline{3-6}  & & **None** & **Light** & **Moderate** & **Strong** \\ \hline [PERSON] et al. [16] & 247 & 43 & 78 & 82 & 44 \\ [PERSON] et al. [17] & 12 & 0 & 1 & 11 & 0 \\ [PERSON] et al. [18] & 16 & 3 & 4 & 8 & 1 \\ [PERSON] et al. [19] & 20 & 3 & 7 & 7 & 3 \\ [PERSON] et al. [20] & 7 & 0 & 1 & 5 & 1 \\ [PERSON] et al. [21] & 7 & 1 & 2 & 0 & 4 \\ [PERSON] et al. [22] & 6 & 0 & 3 & 3 & 0 \\ [PERSON] et al. [10] & 15 & 3 & 5 & 4 & 3 \\ Sum & 330 & 53 & 101 & 120 & 56 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Data sources.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
\begin{tabular}{c} **Rockburst** \\ **Label** \\ \end{tabular} & **Sign** & **Failure Characteristics** \\ \hline None & I & There is no sound of rockbursting or rock falling. \\ \hline Light & II & The rock surrounding the area displays signs of spalling, cracking, or striping. There is no evidence of ejection, and the sound is weak. \\ \hline Moderate & III & The rocks surrounding the area exhibit significant deformation and fracturing, resulting in loose rock chips and sudden destruction. This is often accompanied by a crunchy squeaking sound, which is common in local caverns within the surrounding rock. \\ \hline Strong & IV & The rocks surrounding the tunnel are severely fractured and suddenly propelled into it, accompanied by strong bursts, roars, air jets, and other storm phenomena. This causes rapid expansion into the deep surrounding rocks.  
The violin plot of the rockburst data set is shown in Figure 2. The violin plot, as a density combination of graphs, can effectively show the overall distribution of data. The width of the graph reflects the uniformity of the data distribution; a wider violin plot indicates that the data are more evenly distributed, while a narrower graph indicates a higher degree of data concentration. The box line portion of the violin plot represents the median and interquartile range of the data, and the density of the scatter reflects the degree of concentration of the data in a certain value interval. By looking at Figure 2, it is clear that there is a category imbalance or sampling bias in the dataset, and the presence of these outliers may be related to the samples that were targeted to specific operating conditions during the collection process.  
Further, the scatter and distribution density plots in Figure 3 demonstrate the data distribution relationships between features and the distribution of each rockburst category on a single feature, revealing significant differences in distribution and magnitude between the categories. Therefore, to address these issues, appropriate data enhancement is particularly necessary in the early stages of data processing.  
Table 3, on the other hand, provides the results of the calculations for each metric (standard deviation, kurtosis, maximum, mean, median, and range) in the statistical analysis.  
Figure 1: Distribution of rockburst categories.  
Figure 2: Violin plot of rockburst data distribution.