Sentence examples for latent projection from inspiring English sources

Finally, the results of optimized MF-ICA were compared with those obtained using multivariate curve resolution-alternating least square (MCR-ALS), multivariate curve resolution-objective function minimization (MCR-FMIN) and heuristic evolving latent projection (HELP) methods.

Methods based on quantitative calibration and pattern recognition are established on the basis of latent projection.

Latent projection has been used in the identification and classification of TCM products by NIRS.

Partial least squares (PLS), partial least-squares discriminant analysis (PLS-DA) and soft independent modeling of class analogy (SIMCA) were all developed from latent projection.

Cluster analysis, PCA and discriminant analysis belong to the unsupervised class whereas latent projection, k-nearest neighbor algorithm (KNN), Fisher linear discriminant analysis (KLDA) and artificial neural networks (ANNs) belong to the supervised class.

Multiple analytical techniques such as headspace solid-phase microextraction, gas chromatography mass spectrometry (GC MS), GC MS coupled with heuristic evolving latent projections, moving subwindow searching, nuclear magnetic resonance spectroscopy, and X-ray single-crystal diffraction analysis have been used to identify essential oils from fresh flowers of S. oblata var.

The desired new coordinates P ¯ ' of the latent point projection are defined the following way: P ¯ ' = P ¯ + T ¯ N (7).

The second step contains movement of the latent points projections towards data points of the corresponding class by adjusting the RBF network.

The coordinates of the Gaussians are computed as a linear combination of Gaussian basis functions and for the point x in the latent space its projection to the data space can be defined as: y = W ϕ x (1).

Orthogonal projection to latent structures – discriminant analysis (OPLS-DA) and projection to latent structures – discriminant analysis (PLS-DA) are methods that use supervised multivariate regression to model and predict data.

After principal component analysis (PCA) analysis with SIMCA-14 (Umetrics, Sweden) and Metaboanalyst online analysis software (www.metaboanalyst.ca/), projection to latent structures discriminate analysis (PLS-DA) and orthogonal projection to latent structures discriminate analysis (OPLS-DA) were carried out to further analysis.