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 ...

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 from Scratch Using Singular Value Decomposition with C# Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on a classical ML technique ...

Sankhyā: The Indian Journal of Statistics, Series A (1961-2002), Vol. 26, No. 4 (Dec., 1964), pp. 329-358 (30 pages) The paper provides various interpretations of principal components in the analysis ...

A very important technique in unsupervised machine learning as well as dimensionality reduction is Principal Component Analysis (PCA). But PCA is difficult to understand without the fundamental ...

The critical desorption pressure is different from the gas production pressure of coalbed methane. Gas production pressure is affected by many factors, but their relationships are not obvious.