Dimensionality reduction techniques like PCA work wonderfully when datasets are linearly separable—but they break down the moment nonlinear patterns appear. That’s exactly what happens with datasets ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Nanoparticulate electrocatalysts for the oxygen reduction reaction are structurally ...
Visualization methods like t-SNE and UMAP are sensitive to hyperparameter selection. scDEED helps find optimal hyperparameter values for dimension reduction methods by minimizing the number of dubious ...
Introduction: A full three-dimensional (3D) microstructure characterization that captures the essential features of a given material is oftentimes desirable for determining critical mechanisms of ...
The rotor system is a core part of rotating machinery equipment. Its safe and reliable operation directly affects the economic benefit of using the equipment and the personal safety of users. To fully ...
Principal Component Analysis (PCA) is a very powerful technique that has wide applicability in data science, bioinformatics, and further afield. It was initially ...
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