High-entropy sulfide data for clustering comparison

<p dir="ltr">Unsupervised machine learning algorithms are applied to two different sets of scanning transmission electron microscope data. Energy dispersive X-ray (EDX) analyses were performed on two different samples, a bulk 6-element sulfide (in the file 0008 - SI HAADF 4000 x Nano.hspy) and a nanoparticulate 7-element sulfide (in file HE03NP1F1.emd).</p><p dir="ltr">Unsupervised clustering was performed using a gaussian mixture model (GMM) and by the HDBSCAN algorithm. This allowed the dataset to be segmented to help automatically identify phase and composition variations within samples with minimal user input.</p><p dir="ltr">The python notebook can be used to open and perform the clustering analysis on both of the attached datatasets.</p>