Figure shows an additional visualization of the UMAP. The overview of Figure is the same as that of Figure because the plotting parameters are the same. However, there is additional roles to highlight the plots. Itis highlights focused on the ZnS, AgGaS2, CuGaS2, and CuInS2 are indicated by pink, red, blue, and green symbols, respectively. Specifically, we chose points related to experimental conditions corresponding to the minimum, median, and maximum HER values. These are plotted as crosses, triangles, and circles. The gray circles represent the other sets present in the training data. By focusing on the trend of the positions of the plots highlighted by the arrows with the corresponding colors, it can be recognized that the directions of the connected arrows in the order of minimum, median, and maximum were different from each other. The circles corresponding to the maximum of the HER of each photocatalyst are also located in different positions on the space of UMAP. Taking the plots of ZnS as an example, the arrow from the cross symbol to the triangular symbol is directed toward the lower-right side. In contrast, the arrow from the triangular symbol to the circular symbol was directed toward the upper left side. This trend is not similar to that of other representative materials (AgGaS2, CuGaS2, and CuInS2). These discrepant trends indicate that the optimal variables for the experimental conditions depend on the composition of the photocatalyst. Additionally, in Figure , the values within the parentheses are the HER values provided in [H2/µmol h -1 ]. These show that the minimum to maximum HER values of ZnS, AgGaS2, CuGaS2, and CuInS2 each change significantly across 100 [H2/µmol h -1 ], indicating that the HER varies significantly depending on the experimental conditions. In other words, for extracting information to optimize the variables related to experimental conditions of a specific composition, dataset corresponding to low HER values (less than 100 [H2/µmol h - 1 ]) included of importance information to improve HER over the composition. If we were to thin out the data with HER less than 100 [H2/µmol h -1 ], we would remove such information about the dependencies on the variables related to experimental conditions and fail to understand them. Therefore, we confirmed the effectiveness of the approach presented in this study, which utilizes all the data without thinning them.