In the conclusion of this three-part series, an ambitious idea becomes a reality, uncovering hidden patterns in decades of historical ...
Understanding the properties of different materials is an important step in material design. X-ray absorption spectroscopy ...
Abstract: Monotone missing data is a common problem in data analysis. However, imputation combined with dimensionality reduction can be computationally expensive, especially with the increasing size ...
Abstract: Principal Component Analysis (PCA) aims to acquire the principal component space containing the essential structure of data, instead of being used for mining and extracting the essential ...
GoPCA is the go-to application for Principal Component Analysis - a fundamental machine learning technique for understanding complex, multivariate data. Whether you're analyzing spectroscopic data, ...
Department of Psychology, SVKM’s Mithibai College of Arts, Chauhan Institute of Science and Amrutben Jivanlal College of Commerce and Economics (Empowered Autonomous), Mumbai, India Introduction: ...
Guangxi Colleges and Universities Key Laboratory of Data Analysis and Computation, College of Mathematics and Computing Science, Guilin University of Electronic Technology, Guilin, China. With the ...
In this study, 57 diverse genotypes of Solanum melongena L. comprising commercial varieties, advanced breeding lines, and wild Solanum accessions maintained as a pure line at the Division of Vegetable ...
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 ...
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 ...
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