IEEE

Improvement of Kernel Principal Component Analysis-Based Approach for Nonlinear Process Monitoring by Data Set Size Reduction Using Class Interval

Abstract: Fault detection and diagnosis (FDD) systems play a crucial role in maintaining the adequate execution of the monitored process. One of the widely used data-driven FDD methods is the ...
IEEE

Blockwise Principal Component Analysis for monotone missing data imputation and dimensionality reduction

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 ...
Scientific Research Publishing

Bankruptcy Prediction in the Polish Banking Industry Using Principal Component Analysis and BP Neural Network ()

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 ...
C&EN

Open-Source Visual Programming Software for Introducing Principal Component Analysis to the Analytical Curriculum

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

IRPCA: An Interpretable Robust Principal Component Analysis Framework for Inferring miRNA–Drug Associations

College of Computer Science and Technology, Qingdao Institute of Software, China University of Petroleum (East China), Qingdao 266580, China State Key Laboratory of Chemical Safety, China University ...
Scientific Research Publishing

Pearson, K. (1901). Principal Components Analysis. The London, Edinburgh, and Dublin Philosophical Magazine and Journal of Science, 6, 559.

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 ...
eLife

RETRACTED: Biases of Principal Component Analysis (PCA) in Physical Anthropology Studies Require a Reevaluation of Evolutionary Insights

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 ...
GitHub

Supervised Independent Subspace Principal Component Analysis (sisPCA)

sispca is a Python package designed to learn linear representations capturing variations associated with factors of interest in high-dimensional data. It extends the Principal Component Analysis (PCA) ...
GitHub

Principal-Component-Analysis-using-R-software

## 'data.frame': 150 obs. of 5 variables: ## $ Sepal.Length: num 5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ... ## $ Sepal.Width : num 3.5 3 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 ...
WNCT

Athletic director frames principal using AI in racist audio clip, police say

(AP) — A high school athletic director in Maryland has been accused of using artificial intelligence to impersonate a principal on an audio recording that included racist and antisemitic comments, ...