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 ...

Principal component analysis (PCA) is a classical machine learning technique. The goal of PCA is to transform a dataset into one with fewer columns. This is called dimensionality reduction. The ...

The search for next-generation electronic materials often starts with studying the Fermi surface, which serves as a map of a ...

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 search for next-generation electronic materials often starts with studying the Fermi surface, which serves as a map of a material's electronic ...

The creation and manufacture of automobiles favor the lightweight, robust, and energy absorbing features of composite materials. Included in this are the braking systems of automobiles. Brake pads and ...