1 Department of Plant Production, College of Agriculture and Food, Qassim University, Buraydah, Qassim, Saudi Arabia 2 Department of Environment and Natural Resources, College of Agriculture and Food, ...

The authors present a critique of current usage of principal component analysis in geometric morphometrics, making a compelling case with benchmark data that standard techniques perform poorly. The ...

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 ...

Abstract: Efficient representations of data are essential for processing, exploration, and human understanding, and Principal Component Analysis (PCA) is one of the most common dimensionality ...

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.

ABSTRACT: Traditional treatment selection of cancers mainly relies on clinical observations and doctor’s judgment, but most outcomes can hardly be predicted. Through Genomics Topology, we use 272 ...