Date of Award
1992
Document Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Computer Science
First Advisor
J. Bush Jones
Abstract
Data analysis (reconstructability analysis) is an area used on a data set which has several variables and a function value to find the most important factor that causes the function values to fall within a desired range. Normal data analysis algorithm (1) finds the most important factor in O (2$\sp{n})$ time. This dissertation introduces a newly developed system of algorithms called the Data Analyzing Tree (DAT) which is designed to either reduce the time complexity or produce more accurate results. DAT-1 uses O $(n\sp2)$ time to produce the same results as the normal data analysis method, and DAT-2 produces the result with a higher fall-into-the-range rate while using the same time complexity as the normal data analysis. Therefore, DAT-1 is suitable to get quick results, and DAT-2 or a higher numbered DAT is suitable to get more accurate results. DATs give more choices of the algorithm, so the users can choose the appropriate algorithm depending on the circumstances.
Recommended Citation
Jung, Won Chan, "Improvement of the Data Analysis Algorithm by Applying the Decision Tree Method." (1992). LSU Historical Dissertations and Theses. 5318.
https://repository.lsu.edu/gradschool_disstheses/5318
Pages
95
DOI
10.31390/gradschool_disstheses.5318