Discover how businesses and government agencies can use capital investment analysis to assess the potential of long-term ...

Simplify complex datasets using Principal Component Analysis (PCA) in Python. Great for dimensionality reduction and ...

Now available in Synopsys' line of Ansys simulation & analysis software, engineers can seamlessly evaluate QuantalRF's high-efficiency antennas in their next-generation wireless designs LAS VEGAS, Jan ...

This population-based study shows that shared and pattern-specific blood biomarkers reflect biological vulnerability ...

Abstract: Probabilistic latent variable models (PLVMs), such as probabilistic principal component analysis (PPCA), are widely employed in process monitoring and fault detection of industrial processes ...

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 ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Mass spectrometry imaging (MSI) is constantly improving in spatial resolving power, ...

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 ...

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 ...