A similar Shapley analysis linked with XGBoost regression was performed for the EtOH conversion as well as for the yields of the other products (Figure ), allowing us to comprehensively understand the roles of the individual elements in the ETB catalysis. Here, we propose a method to visualize such a comprehensive understanding based on a force-directed network layout. More specifically, an elemental node and a performance metric node were linked according to the Shapley's global feature importance as determined in Figures and, where the larger the feature importance is, the more the two nodes attract with each other. The thickness of the edge linking the two nodes also represents the feature importance, while the edge color corresponds to the direction of the impact acquired from the local feature importance analysis of Figures 6b and S5 (green: positive; blue: negative). This visualization shown in Figure gives us a wholesome understanding into the complex interplay between elements and reactions in ETB catalysis. At first glance, elements such as Zn, Hf, Mg and Y are found nearby the BD yield with the corresponding edge green-colored, indicating a strong positive impact. Among these, Hf and Y have a negative impact on the AcH yield, suggesting their role in converting AcH to butadiene. Zn, in contrast, has a positive impact on the AcH yield, consistent with its well-known role in converting EtOH into AcH. The elements such as Al, Mo, Nb, and Cu are positively related to the ethylene yield, so that they tended to be eliminated during the evolution (cf. Figure ). Thus, network visualization of Shapley's feature importance helps to intuitively understand the catalytic roles of the individual elements. interdependence between these elements arises from the complex reaction mechanism of ETB, and the literature studies mentioned above partially explain the significance of the co-presence of elements such as Zn, Hf, Y, Zr, and Mg in achieving higher BD yields. However, the current study is the first to explore the interdependence of 14 elements, which is significantly larger than the two or three elements discussed in the literature. Each of these elements plays a unique catalytic role in the complex mechanism of the ETB catalysis, allowing for fine-tuning of EtOH conversion and product distributions. This suggests that the methodology employed in this study can be effectively applied to other complex catalysis, similar to ETB.