Dataset and Python Scripts for Machine-Learning Prediction of Aggregation-Induced Emission Energies

This repository contains the curated dataset and Python scripts used for machine-learning prediction of aggregation-induced emission energies of AIE-active organic luminogens and metal complexes. The deposited files include curated SMILES strings, source URLs, reported emission wavelengths, converted emission energies, RDKit physicochemical descriptors, Morgan fingerprint-based molecular-space analysis data, and Python scripts for Gaussian process regression, SHAP analysis, Morgan fingerprint baseline comparison, PCA/UMAP visualization, and leave-one-cluster-out validation.