Principal component analysis is central to the study of multivariate data. It continues to be the subject of much research, ranging from new model-based approaches to algorithmic ideas from neural networks. It is extremely versatile with applications in many disciplines including computer science, psychology, chemistry, and atomspheric science.
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Principal component analysis is central to the study of multivariate data. It continues to be the subject of much research, ranging from new model-based approaches to algorithmic ideas from neural networks. It is extremely versatile with applications in many disciplines including computer science, psychology, chemistry, and atomspheric science.
Read Less