Abstract: While broadband dielectric spectroscopy enables label-free analysis of biological and chemical materials, extracting multiple concentrations from the data has remained a challenge. This work ...

ABSTRACT: This study applies Principal Component Analysis (PCA) to evaluate and understand academic performance among final-year Civil Engineering students at Mbeya University of Science and ...

I'm always frustrated when deep learning libraries (or books on deep learning libraries) have an example for classification but not regression. I realize that for the experienced user, it's easy to ...

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 ...

This paper develops a procedure for uncovering the common cyclical factors that drive a mix of stationary and nonstationary variables. The method does not require knowing which variables are ...

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.