Welcome to the AutoClass C Documentation! The documentation is divided into a basic core that most users will need to at least skim through, and various other supporting documentation. BASIC DOCUMENTATION: preparation-c.text How to prepare data for use by AutoClass search-c.text How to run AutoClass to find classifications. reports-c.text How to examine the classification in various ways. interpretation-c.text How to interpret AutoClass results. checkpoint-c.text Protocols for running a checkpointed search. prediction-c.text Use classifications to predict class membership for new cases. SUPPORTING DOCUMENTATION: classes-c.text What classification is all about, for beginners. models-c.text Brief descriptions of the model term implementations. kdd-95.ps Postscript file containing: P. Cheeseman, J. Stutz, "Bayesian Classification (AutoClass): Theory and Results", in "Advances in Knowledge Discovery and Data Mining", Usama M. Fayyad, Gregory Piatetsky-Shapiro, Padhraic Smyth, & Ramasamy Uthurusamy, Eds. The AAAI Press, Menlo Park, expected fall 1995. % ghostview kdd-95.ps or % lpr kdd-95.ps tr-fia-90-12-7-01.ps Postscript file containing: R. Hanson, J. Stutz, P. Cheeseman, "Bayesian Classification Theory", Technical Report FIA-90-12-7-01, NASA Ames Research Center, Artificial Intelligence Branch, May 1991 (the figures are not included, since they were inserted by "cut-and-paste" methods into the original "camera-ready" copy -- this will be corrected in the future) % ghostview tr-fia-90-12-7-01.ps or % lpr tr-fia-90-12-7-01.ps