Computation of training set (X^T * W * X) and (X^T * W * Y) or (X^T * X) and (X^T * Y) in a cross-validation setting using the fast algorithms by Engstrøm and Jensen (2025). FELBuilder is an automated ...

Part II: Unsupervised machine learning in R to cluster and identify candidate countries for international expansion, using PCA, K-Means, and DBSCAN.

Introduction: Intravenous (IV) infusion is overused in Chinese hospitals, and a tool to appraise its appropriateness quantitatively and qualitatively is lacking. This study aimed to develop a ...

Inside living cells, mitochondria divide, lysosomes travel, and synaptic vesicles pulse—all in three dimensions (3Ds) and constant motion. Capturing these events with clarity is vital not just for ...

The evaluation of genetic diversity in germplasm resources is fundamental to crop breeding. A total of 183 oat germplasm resources were evaluated through field trials at Xinjin District and Shandan ...

Principal component analysis (PCA) is one of the most common exploratory data analysis techniques with applications in outlier detection, dimensionality reduction, graphical clustering, and ...

ABSTRACT: This article examines the effect of economic vulnerability on inclusive growth across 49 developing countries from 1991 to 2020, focusing on the mitigating role of agricultural structural ...

ABSTRACT: This study investigates the use of a decision tree classification model, combined with Principal Component Analysis (PCA), to distinguish between Assam and Bhutan ethnic groups based on ...

The authors present a critique of current usage of principal component analysis in geometric morphometrics, making a compelling case with benchmark data that standard techniques perform poorly. The ...