Short description:
Dr. Eric C. Sayre, PhD is a scientist, statistician, author and programmer. Eric is well-published, with over 100 publications since 1997. In Eric's PhD research, he developed a new method of unsupervised learning (hypothesis generation) designed specifically for mixed-type data (continuous, ordinal, nominal, binary symmetric and binary asymmetric), along with data mining software to perform the analyses. Variable-Weighted Ultrametric Optimization for Mixed-Type Data (VWUO-MD) is useful in identifying new, complex relationships between variables of many different kinds, for example between a multitude of health conditions, socio-economic and geographic factors, and health services utilization patterns. VWUO-MD is a valuable tool for exploiting the increasing multitude of highly multivariate, mixed-type databases available to researchers and industry, in developing new, previously unthought-of hypotheses.

Visit www.ericsayre.com for more information, an abstract, links to the complete PhD thesis and user's guide, and a FREE TRIAL version of the software.

WARNING: To read the Software Performance Limitations and End User Software License Agreement to which you are agreeing when purchasing this program, and to download a FREE TRIAL version (recommended), visit www.ericsayre.com BEFORE purchasing this program.