# Slope Stability Prediction Based on Incremental Learning Bayesian Model and Literature Data Mining
## 3 Results  
### Descriptive Analysis  
To investigate the distribution patterns and data structures of each parameter in Dataset I, violin plots comprising box plots and density estimates were created, as shown in Figure 2. The first and third quartiles are marked by the top and bottom of the box plot's solid line, respectively. Median values are indicated by the solid lines between the quartile markers, while solid black dots denote average values. Extremes of data, including maximum and minimum values, are represented by the tips of the vertical whisker lines. Additionally, the violin plots provide visual information about data density. A wider section signifies higher density, whereas a narrower section indicates lower density. Figure 2 shows that height and cohesion exhibit concentrated distributions with some individual extreme data points. Height data predominantly fall within 20-150 m, encompassing low, medium, high, and super-high cases. Both stable and unstable slopes exhibit similar violin shapes. Slope angle data demonstrate a relatively even distribution, covering mild, medium, steep, and sharp slopes, with similar violin shapes for stable and unstable slopes. Regarding unit weight data, unstable slopes primarily cluster between 19 and 22 kN/m\({}^{-3}\), while stable slopes concentrate between 25 and 28 kN/m\({}^{-3}\), indicating higher values for stable slopes. Cohesion data fall within 10-40 kPa, showing similar shapes for stable and unstable slopes. The angle of internal friction data shows unstable  
slopes mainly between 21\({}^{\circ}\) and 29\({}^{\circ}\) and stable slopes between 29\({}^{\circ}\) and 36\({}^{\circ}\), with higher values for more stable slopes. The pore water ratio data are concentrated in the 0-0.15 kPa and 0.25-0.3 kPa ranges, with similar shapes for stable and unstable slopes; however, stable slopes are more closely distributed in the 0.25-0.3 kPa interval. The dataset aligns with other research, indicating a balanced construction, reasonable variable distribution, and minimal outliers. The data, mean, and median values for each variable group are presented in Table 3. The mean and median values differ notably between stable and failure states, with height and angle of internal friction exhibiting the most significant variations. Under stable conditions, the mean and median heights are 24.67 and 26.2, while for the failed state, they are 21.29 and 21.1, indicating deviations of 3.38 and 5.1, respectively. Similarly, the mean and median angles of internal friction in stable conditions are 31.71 and 33, contrasting with 25.8 and 26 for the failed state, indicating deviations of 5.91 and 7, respectively. Additionally, the mean and median values of the six variables in the stable state are higher than those in the failed state. The correlation matrix plot in Figure 3 was analyzed to clarify the relationships among the six parameters and their correlation with slope stability classification (SSC). The plot displays the data distribution and Pearson correlation coefficients between variables. In the figure, the red circles represent unstable slope cases, while the green circles represent stable slope cases. The red lines are curves derived from the distribution fitting of two parameters. Based on other research, a Pearson correlation coefficient exceeding 0.7 may \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Actual State of the Slope**} & \multicolumn{8}{c}{**Slope Stability Prediction Index**} \\ \cline{2-7}  & **Features** & \(\mathbf{H}(\mathbf{m})\) & \(\mathbf{\beta}(^{\circ})\) & \(\mathbf{\gamma}(\mathbf{kN/m^{3}})\) & \(\mathbf{C}(\mathbf{kPa})\) & \(\mathbf{\varphi}(^{\circ})\) & _ru_ \\ \hline Stable & \multirow{2}{*}{Mean value} & 133.98 & 36.74 & 24.67 & 39.31 & 31.71 & 0.18 \\ Failure & & 87.51 & 33.47 & 21.29 & 34.97 & 25.80 & 0.15 \\ Stable & \multirow{2}{*}{Median} & 89.25 & 37.15 & 26.20 & 35.20 & 33.00 & 0.25 \\ Failure & & value & 50.50 & 32.15 & 21.10 & 24.50 & 26.00 & 0.00 \\ \hline \hline \end{tabular}
\end{table}