When considering nonadiabatic molecular dynamics (NAMD) for data generation, a sequential array of frames representing diverse molecular configurations is produced. These frames can be condensed into vectors, enriched with quantum properties computed during the dynamics, creating a comprehensive dataset of molecular behaviors. As time scales extend, the dataset becomes increasingly extensive and intricate. The surface hopping approximation further adds complexity by increasing data volume through the requirement of multiple independent trajectories, which in turn increases system dimensionality and makes advanced statistical methods essential for pattern extraction. In nonadiabatic molecular dynamics (NAMD) simulations, multiple electronic states and their associated potential energy surfaces are involved. As molecular trajectories evolve over time, they encounter regions of conical intersections or surface hopping, where transitions between states occur.