The subject of data-driven modeling has been addressed in various disciplines such as statistics, pattern recognition, signal processing, genomics, artificial neural networks, machine learning, and data mining, which adopt specialized terminology and conceptual frameworks to motivate various learning algorithms, in spite of the close similarity (equivalence) between actual algorithms. The main commonality between these methodologies is that they all...