Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 2 of 2
Full-Text Articles in Physical Sciences and Mathematics
Directed Extended Dependency Analysis For Data Mining, Thaddeus T. Shannon, Martin Zwick
Directed Extended Dependency Analysis For Data Mining, Thaddeus T. Shannon, Martin Zwick
Systems Science Faculty Publications and Presentations
Extended dependency analysis (EDA) is a heuristic search technique for finding significant relationships between nominal variables in large data sets. The directed version of EDA searches for maximally predictive sets of independent variables with respect to a target dependent variable. The original implementation of EDA was an extension of reconstructability analysis. Our new implementation adds a variety of statistical significance tests at each decision point that allow the user to tailor the algorithm to a particular objective. It also utilizes data structures appropriate for the sparse data sets customary in contemporary data mining problems. Two examples that illustrate different approaches …
An Overview Of Reconstructability Analysis, Martin Zwick
An Overview Of Reconstructability Analysis, Martin Zwick
Systems Science Faculty Publications and Presentations
This paper is an overview of reconstructability analysis (RA), a discrete multivariate modeling methodology developed in the systems literature; an earlier version of this tutorial is Zwick (2001). RA was derived from Ashby (1964), and was developed by Broekstra, Cavallo, Cellier Conant, Jones, Klir, Krippendorff, and others (Klir, 1986, 1996). RA resembles and partially overlaps log‐line (LL) statistical methods used in the social sciences (Bishop et al., 1978; Knoke and Burke, 1980). RA also resembles and overlaps methods used in logic design and machine learning (LDL) in electrical and computer engineering (e.g. Perkowski et al., 1997). Applications of RA, like …