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Full-Text Articles in Physical Sciences and Mathematics
Exploratory Reconstructability Analysis Of Accident Tbi Data, Martin Zwick, Nancy Ann Carney, Rosemary Nettleton
Exploratory Reconstructability Analysis Of Accident Tbi Data, Martin Zwick, Nancy Ann Carney, Rosemary Nettleton
Systems Science Faculty Publications and Presentations
This paper describes the use of reconstructability analysis to perform a secondary study of traumatic brain injury data from automobile accidents. Neutral searches were done and their results displayed with a hypergraph. Directed searches, using both variable-based and state-based models, were applied to predict performance on two cognitive tests and one neurological test. Very simple state-based models gave large uncertainty reductions for all three DVs and sizeable improvements in percent correct for the two cognitive test DVs which were equally sampled. Conditional probability distributions for these models are easily visualized with simple decision trees. Confounding variables and counter-intuitive findings are …
Data Near Here: Bringing Relevant Data Closer To Scientists, Veronika M. Megler, David Maier
Data Near Here: Bringing Relevant Data Closer To Scientists, Veronika M. Megler, David Maier
Computer Science Faculty Publications and Presentations
Large scientific repositories run the risk of losing value as their holdings expand, if it means increased effort for a scientist to locate particular datasets of interest. We discuss the challenges that scientists face in locating relevant data, and present our work in applying Information Retrieval techniques to dataset search, as embodied in the Data Near Here application.
Reconstructability Analysis With Fourier Transforms, Martin Zwick
Reconstructability Analysis With Fourier Transforms, Martin Zwick
Systems Science Faculty Publications and Presentations
Fourier methods used in two‐ and three‐dimensional image reconstruction can be used also in reconstructability analysis (RA). These methods maximize a variance‐type measure instead of information‐theoretic uncertainty, but the two measures are roughly collinear and the Fourier approach yields results close to that of standard RA. The Fourier method, however, does not require iterative calculations for models with loops. Moreover, the error in Fourier RA models can be assessed without actually generating the full probability distributions of the models; calculations scale with the size of the data rather than the state space. State‐based modeling using the Fourier approach is also …
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 …
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 …