Advances in principal component analysis / / edited by Fausto Pedro García Márquez.
This book describes and discusses the use of principal component analysis (PCA) for different types of problems in a variety of disciplines, including engineering, technology, economics, and more. It presents real-world case studies showing how PCA can be applied with other algorithms and methods to...
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| Place / Publishing House: | London, England : : IntechOpen,, 2022. |
| Year of Publication: | 2022 |
| Language: | English |
| Physical Description: | 1 online resource (252 pages) |
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Table of Contents:
- 1. The Foundation for Open Component Analysis: A System of Systems Hyper Framework Model
- 2. Identification of Multilinear Systems: A Brief Overview
- 3. Evaluation of Principal Component Analysis Variants to Assess Their Suitability for Mobile Malware Detection
- 4. Principal Component Analysis and Artificial Intelligence Approaches for Solar Photovoltaic Power Forecasting
- 5. Variable Selection in Nonlinear Principal Component Analysis
- 6. Space-Time-Parameter PCA for Data-Driven Modeling with Application to Bioengineering
- 7. Principal Component Analysis in Financial Data Science
- 8. Determining an Adequate Number of Principal Components
- 9. Spatial Principal Component Analysis of Head-Related Transfer Functions and Its Domain Dependency
- 10. Prediction Analysis Based on Logistic Regression Modelling
- 11. On the Use of Modified Winsorization with Graphical Diagnostic for Obtaining a Statistically Optimal Classification Accuracy in Predictive Discriminant Analysis
- 12. Mode Interpretation of Aerodynamic Characteristics of Tall Buildings Subject to Twisted Winds.