On Factor Analysis and Fisher's Linear Discriminant Analysis

Automics: an integrated platform for NMR-based metabonomics spectral processing and data analysis

“…Automics provides nine different pattern recognition methods for data analysis. These methods include feature (variable) selection method (Fisher's criterion (FC) [ 35 ]), data reduction method (principal component analysis (PCA), linear discriminant analysis (LDA) [ 36 ], uncorrelated linear discriminant analysis (ULDA) [ 37 , 38 ]), unsupervised clustering method (K-Mean Clustering (K-Mean) [ 39 ]), and supervised regression and classification methods (partial least squared analysis (PLS) [ 40 , 41 ], K nearest neighbor classification (KNN) [ 42 ], soft independent modeling of class analogy (SIMCA) [ 43 ] and support vector machine (SVM) [ 44 ]).…”