Results are presented from Principal Components Analysis of three data matrices (pollen concentration per c.c., percentages of total pollen, and analyses for eight or nine chemical elements) of c.

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 ...

As a multivariate statistical method, the Principal component analysis has been applied to many research fields. Recently, a seismological study successfully introduced the Principal component ...

Several measurement techniques used in the life sciences gather data for many more variables per sample than the typical number of samples assayed. For instance, DNA microarrays and mass spectrometers ...