Michalski, Ryszard S.Kaufman, Kenneth A.2006-11-032006-11-032000-03Kaufman, K. and Michalski, R. S., "The AQ18 System for Machine Learning and Data Mining System: An Implementation and User's Guide," Reports of the Machine Learning and Inference Laboratory, MLI 00-3, George Mason University, Fairfax, VA, 2000.https://hdl.handle.net/1920/1459This report is a comprehensive user's guide for AQ18, an environment for natural induction, machine learning and knowledge discovery. By natural induction is meant a form of inductive inference which strives to induce data descriptions that are most natural and comprehensible to people. This feature is achieved by employing a highly expressive description language (attributional calculus). Along with a learning for determining attributional rulesets from examples, or for incrementally improving the previously learned rulesets through new examples, AQ18 also incorporates a ruleset testing module (ATEST) and a module for selecting the best attributes for a given learning problem (PROMISE).1967 bytes597732 bytes187664 bytestext/xmlapplication/postscriptapplication/pdfen-USMachine learningData miningInductive inferenceLearning from examplesTechnical report