Outcome from NMFk analysis. (A) The Silhouette-Reconstruction
Download scientific diagram | Outcome from NMFk analysis. (A) The Silhouette-Reconstruction criterium (see the Methods Section). On the x-axis is denoted the number of basis lipid configurations and on the y-axis-the average Silhouettes (right y-axis, red marking) as from publication: Unsupervised Machine Learning for Analysis of Coexisting Lipid Phases and Domain Growth in Biological Membranes | Phase separation in mixed lipid systems has been extensively studied both experimentally and theoretically because of its biological importance. A detailed description of such complex systems undoubtedly requires novel mathematical frameworks that are capable to decompose and | Unsupervised Machine Learning, Lipids and Biological Membranes | ResearchGate, the professional network for scientists.
Outcome from NMFk analysis. (A) The Silhouette-Reconstruction criterium
Blind source separation for groundwater pressure analysis based on nonnegative matrix factorization - Alexandrov - 2014 - Water Resources Research - Wiley Online Library
NMFk with resampling of initial matrix, A
Average reconstruction error (red) and the average Silhouette width
Average reconstruction error (red) and the average Silhouette width
Uncovering novel mutational signatures by de novo extraction with SigProfilerExtractor
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Fe-Ga-Pd data: a) Heat map of the intensity of the XRD data. b) The
Outcome from NMFk analysis. (A) The Silhouette-Reconstruction criterium
Outcome from NMFk analysis. (A) The Silhouette-Reconstruction criterium
Unsupervised Machine Learning for Analysis of Phase Separation in Ternary Lipid Mixture
NMFk with resampling of initial matrix, A
a) Silhouette values from clustering (♢) and NMF reconstruction error
