Filtering corrupted data at influencing points with a statistical catalyst agent (original) (raw)

2003

Abstract

Catalyst agent (CA) is the name given to a new concept in which artificial data points are introduced with an intension of later filtering them togenther with massive amount of corrupted data that mask possible relationship between variables. Use of CA method could sharpen and extract valuable relationships hidden in massive datasets. This paper explores the potential of CA method in the context of data mining and modeling of massive datasets is evaluated. The concept is illustrated with a simple linear regression model and CAs with influencing effects on X and Y directions. The introduction of so-called X-influencing and Y-influencing datasets allows extraction of relationships hidden in massive datasets. The potential for future improvement of the technique in multivariate context is discussed. While nothing has been reported in this area of research in the past, the method lays the foundation for a new era of future statistical research

Shelton Peiris hasn't uploaded this paper.

Let Shelton know you want this paper to be uploaded.

Ask for this paper to be uploaded.