Researchers have developed ProD, a visualizable filter feature selection method that ranks variables by measuring the ...

The increasing diversity of scientific and engineering data has driven the development of flexible techniques for inferring probability distributions without assuming a specific parametric family.

Kernel density estimation (KDE) is a cornerstone of non-parametric statistics, offering a flexible means to infer an underlying probability density from finite samples without assuming a predetermined ...

Authors Jeff Tracey-PR, James K. Sheppard, Glenn K. Lockwood, Amit Chourasia, Mahidhar Tatineni, Robert N. Fisher, Robert S. Sinkovits ...