## 3 Results and Discussion
### Feature Importance for Prediction of Nominal Stress  
The Nominal Stress can be predicted for the ZYX, Angle, and All orientations with a higher prediction accuracy (0.902, 0.906, and 0.964 respectively) than for Tensile Modulus. For example, the list of the features based on the relative importance in the ZYX orientation for Nominal stress is different (see Figure 9a) from the list proposed for Tensile Modulus. The Gradient Boost Regressor algorithm has weighted number of mesh triangles as the most important feature, which is followed by such features as surface, central, and minimal coordinates in the X-axis, number of mesh triangles, and volume, in the listed order. The positioning of the specimens is also highlighted by the algorithm in terms of the coordinates in the X-axis and maximal coordinate in the Z-axis. Since the connection between STL model properties and part positioning has been described for Tensile Modulus as a possible way of defining temperature distribution in the build chamber, with special attention to the energy concentration, similar trends are observed in models developed to predict Nominal Stress. The number of mesh triangles influences the way a part is sliced on the layer, which results in the construction of parts' contours at each layer for an additive machine, and thus contributes to the energy concentration for each specific part. This assumption is in good agreement with previously published studies [42; 43]. However, when it comes to the analysis of features' importance for the developed model in Angle orientation, STL model properties are still in the list of being important, but their contribution is less significant compared to the ZYX/All orientations (see Figure 9b). One of the reasons why volume and surface features are among the least significant for the developed model can be the distribution of actual values for all specimens in Angle orientation. Thus, surface values are in the  
Figure 8: Visualization of Tensile Modulus for ZYX orientation (**a**) As a function of central coordinates in the X- and Y-axes in mm. (**b**) As a function of central coordinates in the X- and Z-axes in mm. range 1401.787-1432.563 mm\({}^{2}\), while the values range for volume is even smaller (1029.925-1035.427 mm\({}^{3}\)). However, the value range for a surface feature for all specimens (without separation on orientations) has a significant difference (e.g., 1381.555-1441.187 mm\({}^{2}\)) compared with volume values (1029.925-1035.427 mm\({}^{3}\)). However, comparison of these ranges raises another question on why such a small range for the volume feature is important for prediction of both Tensile Modulus and Nominal Stress in the ZYX orientation. In order to be able to answer this question, more experimental work is needed to be done in the future, where the variation of the STL model properties should be of main concern. Another assumption could be made by looking at the prediction accuracy for the linear model, which is equal to 0.867 out of 1. This could mean that the linear correlation between investigated features and Nominal Stress is present for angle orientation, while the correlation between STL model properties and Nominal Stress is absent. Results obtained when all orientations are analyzed together are illustrated in Figure 10. As can be seen, specimens' positions in the X-axis is listed as the most important feature, and special attention is paid to the minimal coordinate in the X-axis. In order to understand better why minimal coordinate in the X-axis is chosen to be more important than, for instance, central or maximal coordinates, there is a need for visualizing how Nominal Stress is dependent on these coordinates.