All sparse PCA models are wrong, but some are useful. Part II: Limitations and problems of deflation
Sign Up to like & getrecommendations! Published in 2020 at "Chemometrics and Intelligent Laboratory Systems"
DOI: 10.1016/j.chemolab.2020.104212
Abstract: Abstract Sparse Principal Component Analysis (sPCA) is a popular matrix factorization approach based on Principal Component Analysis (PCA). It combines variance maximization and sparsity with the ultimate goal of improving data interpretation. A main application… read more here.
Keywords: pca models; part; analysis; wrong useful ... See more keywords
Animal Models for Radiotherapy Research: All (Animal) Models Are Wrong but Some Are Useful
Sign Up to like & getrecommendations! Published in 2021 at "Cancers"
DOI: 10.3390/cancers13061319
Abstract: The distinguished statistician, George E [...]. read more here.
Keywords: models radiotherapy; animal models; wrong useful; models wrong ... See more keywords