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 ...

Simplify complex datasets using Principal Component Analysis (PCA) in Python. Great for dimensionality reduction and ...

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 ...

Journal of the Royal Statistical Society. Series C (Applied Statistics), Vol. 32, No. 3 (1983), pp. 267-275 (9 pages) In applying principal components for reducing the dimension of the data before ...

Wireline logging plays a critical role in coalbed methane exploration. However, the lack of crucial log data, such as neutron and sonic logs, makes coalbed methane exploration difficult. In this paper ...