Correlation and association analyses are one of the most widely used statistical methods in
research fields, including microbiome and integrative multiomics studies. Correlation and …

The water resources-water environment carrying capacity (WR-WECC) is an important
indicator for judging the regional macro-control ability of water resources. The nature-based …

Learning graph embeddings for high-dimensional data is an important technology for
dimensionality reduction. The learning process is expected to preserve the discriminative …

Generalized linear latent variable models (GLLVMs) have become mainstream models in
this analysis of correlated, m‐dimensional data. GLLVMs can be seen as a reduced‐rank …

Nowadays, graph-based dimensionality reduction approaches have become more and
more popular due to their successful utilization for classification and clustering tasks. In …

With the rapid development of 5G communication technology, the data in the Internet of
Medical Things (IoMT) application systems exhibits complex characteristics such as large …

This report describes how image processing harnessed to multivariate analysis techniques
can be used as a bio-analytical tool for mastitis screening in cows using milk samples …

Graph embedding plays an important role in dimensionality reduction for processing the
high-dimensional data. In graph embedding, its keys are the different kinds of graph …

To deal with semi-supervised feature selection tasks, this paper presents a recursive feature
retention (RFR) method based on a neighborhood discriminant index (NDI) method (a …

As the major research in pattern recognition, unsupervised dimension reduction is a
challenging problem because of no label information. Most unsupervised dimension …