## 2 Materials and Methods
### Characteristics of the Database
#### 2.1.5 Feature Correlation  
The fifteen parameters presented above were generally not or slightly correlated with each other. The Spearman correlation coefficient was used as a measure. This coefficient shows any, including the nonlinear, monotonic relationship between two variables, ranging between \(-\)1 and 1. The sign of the Spearman correlation coefficient indicates whether it is a positive or negative monotonic relationship. Only a few parameters in the database were strongly positively correlated, for example, the distance from the remnant and the time since it was left, and the distance from the destressing seam and the time that had elapsed since its extraction. The Spearman correlation coefficient in these cases equaled 0.97 and 0.7, respectively. Such a correlation resulted from the fact that shallower seams are usually excavated earlier than those deposited deeper. The energy of the tremor and the associated PPV were moderately positively correlated, with the Spearman correlation coefficient being 0.53. This is somewhat understandable because the PPV is proportional to the energy of the tremor. Of course, distance from the tremor focus and the directionality of seismic wave radiation must also be considered. Considering only rock bursts classified as such following the applicable mining regulations, the Spearman correlation coefficient between the GEO and tremor energy was 0.44. The correlation between the fifteen distinguished parameters and the occurrence of rock bursts in the database was also determined. It should be noted that rock bursts accounted for approximately 8.5% of the dataset. In most of the remaining cases, despite high PPV values and the rock mass's proneness to rock bursts, rock bursts did not occur. This does not prove the lack of usefulness of the analyzed parameters, but a complicated and nonlinear dependence of the occurrence of rock bursts. Strong tremors are often not associated with rock bursts in underground mining openings, even when drilled in rock masses prone to rock bursts. Moreover, in the case of the GEO system, it should be emphasized that it was created based on rock bursts classified according to the Polish mining regulations. Individual classification criteria in the GEO system have been adopted for rock bursts regarding dynamic phenomena caused by tremors. As a result, openings lost their functionality and thus were significantly damaged or destroyed. In this article, even local damage to the excavation was considered a rock burst. In an excavation drilled in a rock mass prone to rock bursts, rock bursts do not have to occur due to a strong tremor. Moreover, such cases are rare in comparison to cases of non-destructive tremors. Additionally, reinforcement of the support or a destressing effect due to blasting can prevent a rock burst, even in rock mass prone to rock burst. The highest value of the Spearman correlation coefficient was for PPV (0.26), followed by the type of excavation (0.22), and GEO index (0.12). The Spearman correlation coefficient for a neighborhood to goals, excessive bed cutting, and reinforcement of the support was 0.11. For the remaining nine parameters, the absolute value of the Spearman correlation coefficient did not exceed 0.1. Negligible negative and positive monotonic relationships were found for five and four features, respectively. A RadViz plot was used to illustrate the cases of rock bursts and cases without destruction and damage to mining openings against the background of the distinguished features with normalized values (Figure 2). The RadViz plot enables the graphical presentation of multidimensional data. In this way, it is possible to determine existing regularities, identify clusters of similar objects, and indicate unusual observations. The separateness of the features was visualized this way. The dataset was highly imbalanced. Using such data may have resulted in the incorrect classification of cases being in the significant minority. To balance the dataset, the adaptive synthetic (ADASYN) algorithm was used.