Sentence examples for methods including principal from inspiring English sources

The purpose of this article is to provide an overview of data reduction methods, including principal components analysis, factor analysis, reduced rank regression, and cluster analysis.

Statistical methods, including principal component analysis (PCA), partial least-square regression (PLS) and discriminant analysis (PLS-DA), were applied to find metabolite patterns related to surgical trauma and postoperative hypoxemia.

As of today, there are many popular linear and non-linear dimensionality reduction methods including principal component analysis, kernel principal components analysis, Isomap, Laplacian Eigenmaps and local linear embedding.

Some common chemometric methods, including principal component analysis (PCA), linear discriminant analysis (LDA) and k-nearest neighbor (kNN) based hierarchical cluster analysis (HCA) were used to test the discriminatory power of the array.

Pattern recognition methods including principal components analysis (PCA), partial least-squared discriminant analysis (PLS-DA), orthogonal partial least-squared discriminant analysis (OPLS-DA) and computational system analysis were integrated to obtain comprehensive metabonomic profiling and pathways of the biological data sets.

Two multivariate methods including principal component analysis (PCA) and hierarchical clustering analysis (HCA) were utilized in this study.

Well-known linear transformation methods include principal component analysis, factor analysis, and projection pursuit.

Commonly applied methods include principal component analysis (PCA), various forms of cluster analysis (CA), and discriminant analysis (DA, both linear and quadratic), followed by more recent (neural network and fuzzy) methods [17], although the application of combined techniques has been reported in the literature [28].

Feature selection methods included principal component analysis (PCA), chisquare, gainratio, inforgain, relief, and SVM recursive feature election (SVM-RFE).

In this paper, we propose a robust decision support tool for detailed production planning based on statistical multivariate method including principal component analysis and logistic regression.

Mehrjoo and Bashiri (2013) proposed a robust decision support tool for detailed production planning based on statistical multivariate method including principal component analysis and logistic regression.