Significados de linear discriminant analysis en inglés

Limited differences were seen on linear discriminant analysis effect size analysis.

Smellprints were analyzed by linear discriminant analysis on principal component reduction.

Using linear discriminant analysis, these five criteria allowed us to build a scaled score.

This metric is used to train a classification model based on linear discriminant analysis.

The intended movement direction was decoded using linear discriminant analysis and a Bayesian classifier.

Statistical analysis was performed using the t test, linear discriminant analysis, and k nearest-neighbor method.

Water signal was quantified and metabolite signals were compared and analyzed using linear discriminant analysis.

A linear discriminant analysis model was selected for the final model of Th2 cell group prediction.

A linear discriminant analysis was performed to further compare the predictive value of the basal hormone levels.

Furthermore, stepwise linear discriminant analysis provided a good classification of the individual patients into the different disease groups.

Multivariate linear discriminant analysis of EEG features with and without accelerometer features was used to classify behavioral state.

Statistical analysis on sensor responses was performed off-line by principal component analysis, linear discriminant analysis and ROC curves.

A classification model based on linear discriminant analysis was trained to distinguish four cell types by their IR spectroscopic fingerprint.

Comparison of the microbial diversity between GCA cases and controls was carried out using hierarchical clustering and linear discriminant analysis of effect size.

An SCS was applied consisting of pre-processing MR magnitude spectra to identify spectral regions of maximal discriminatory value, and cross-validated linear discriminant analysis.

Forward linear discriminant analysis (LDA) was used to select the 10 spectral bands with the highest contribution to classifications of the three species.