1 Department of Plant Production, College of Agriculture and Food, Qassim University, Buraydah, Qassim, Saudi Arabia 2 Department of Environment and Natural Resources, College of Agriculture and Food, ...

Introduction: This study investigates an approach for defect characterization in non-ferromagnetic materials by combining Pulsed Alternating Current Field Measurement (PACFM) with Principal Component ...

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 ...

PCA is an important tool for dimensionality reduction in data science and to compute grasp poses for robotic manipulation from point cloud data. PCA can also directly used within a larger machine ...

Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on a classical ML technique that transforms a dataset into one with fewer columns, useful for creating a graph of ...

Abstract: Efficient representations of data are essential for processing, exploration, and human understanding, and Principal Component Analysis (PCA) is one of the most common dimensionality ...

This paper develops a procedure for uncovering the common cyclical factors that drive a mix of stationary and nonstationary variables. The method does not require knowing which variables are ...