The use of machine learning program LERS-LB 2.5 in knowledge acquisition for expert system development in nursing.

LERS-LB (Learning from Examples using Rough Sets Lower Boundaries) is a computer program based on rough set theory for knowledge acquisition, which extracts patterns from real-world data in generating production rules for expert system development. From LERS-LB evaluation of an SPSS-X data file containing data for recovery room patients, it was concluded that both statistical data files and existing databases can be converted to decision-table format needed by LERS-LB, but it is less desirable to work with statistical files than a well-developed database. It was also concluded that choosing a well-developed database and checking it thoroughly for accuracy and completeness should be done before running LERS-LB, or other learning programs, to avoid problems with data errors.