Gaussian functions are situated around each bond length and/or bond angle for specific atoms. Thus, a value of Δ(𝑥 𝑖 , 𝑥 𝑗 ) = 0 indicates that the structures are identical and low values determine high similarity. Consequently, one can speed up the ML modeling of a target configuration by training only on a small data set. Cluster formation inevitably involves both enthalpy (Δ𝐻) and entropy (Δ𝑆) changes, and hence the clustering free energy (e.g., Δ𝐺 = Δ𝐻 -𝑇Δ𝑆 ) increases with increasing temperature (𝑇). Weakly bonded clusters thus typically require low temperature and/or high vapor concentrations to form in the gas phase, while strongly bonded clusters may also be formed at room temperature and trace concentrations of the vapors. Figure Neither the binding energy nor the reactivity (e.g., proton transfer) alone are sufficient to determine how straightforward the configurational sampling (CS) process is for a given clustering system. Over several years, JKCS has been used to study various clusters and their properties. Based on these studies, we present typical examples of molecular cluster properties that complicate CS compared to a reference case of a nonreactive, one-component, crystal-like cluster with a single low-energy configuration, formed from rigid, closed-shell monomers with only one conformer. This reference case can be, for example, a water cluster at a very low temperature, i.e., an ice crystal. Clusters fall into one or several of the following categories: