Overall, the degree of clustering across categories escalates from binary to quaternary systems with the increasing order of complexity and chemical diversity inherent in higher-order compounds. As transition to quaternary compounds, the distinct characteristics of each class become more salient. It is worth highlighting that the dimension reduction, resulting from the unsupervised learning algorithms, demonstrates cohesive clustering that corresponds to our classification with a striking clustering of the standard and missing compositions.