The purpose of principal component analysis is to derive a small number of independent linear combinations (principal components) of a set of variables that retain as much of the information in the ...

Transforming a dataset into one with fewer columns is more complicated than it might seem, explains Dr. James McCaffrey of Microsoft Research in this full-code, step-by-step machine learning tutorial.

A good way to see where this article is headed is to take a look at the screen shot of a demo program shown in Figure 1. The demo sets up a dummy dataset of six items: [ 5.1 3.5 1.4 0.2] [ 5.4 3.9 1.7 ...

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 ...

The level of difficulty in designing electro-technique devices has increased, owing to thermal stress. With the development of electric vehicles and electric aircraft, and to keep up with the recent ...

A recent study saw the Thermo Scientific™ K-Alpha™ X-ray Photoelectron Spectrometer (XPS) System employed in an investigation ...