Symbolic methodology for numeric data mining

Symbolic methodology for numeric data mining

Currently statistical and artificial neural network methods dominate in data mining applications. Alternative relational (symbolic) data mining methods have shown their effectiveness in robotics, drug design, and other areas. Neural networks and decision tree methods have serious limitations in capturing relations that may have a variety of forms. Learning systems based on symbolic first-order ...

Symbolic Methodology in Numeric Data Mining: Relational Techniques for Financial Applications

Currently statistical and artificial neural network methods dominate in financial data mining. Alternative relational (symbolic) data mining methods have shown their effectiveness in robotics, drug design and other applications. Traditionally symbolic methods prevail in the areas with significant nonnumeric (symbolic) knowledge, such as relative location in robot navigation. At first glance, st...

Hybrid Symbolic-Numeric Methodology: Views and Visions

We used computer aided symbolic computation in our previous papers to explore solutions of partial differential equations in a way that involves a synergistic application of symbolic and numeric methodologies. Here we review the results thus far and present a few examples of this emerging methodology applied to the nonlinear Burgers equation. The continued development of the hybrid methodology ...

Symbolic-Numeric Algebra for Polynomials

Numeric versus Symbolic Computation

Twentyfive years ago when I studied Physics, only one of the students who participated in a laboratory course that I took was possessing one of the first calculators to process the data we were obtaining. Believe it or not, everybody else, including me, had to use a slide-rule for this purpose. Nowadays, the calculator is used by everybody, by far not only for academic purposes. Hence it is the...