Diagnostic Test Approaches to Machine Learning and Commonsense Reasoning Systems

Marc Notes: Includes bibliographical references and index.; This book analyzes and compares the existing and most effective algorithms for mining through logical rules and shows how these approaches use shared concepts for mining logical rules, including item, item set, transaction, frequent itemset, maximal itemset, generator (non-redundant or irredundant itemset), closed itemset, support, and confidence--; Provided by publisher. Publisher Marketing: The consideration of symbolic machine learning algorithms as an entire class will make it possible, in the future, to generate algorithms, with the aid of some parameters, depending on the initial users' requirements and the quality of solving targeted problems in domain applications. Diagnostic Test Approaches to Machine Learning and Commonsense Reasoning Systems surveys, analyzes, and compares the most effective algorithms for mining all kinds of logical rules. Global academics and professionals in related fields have come together to create this unique knowledge-sharing resources which will serve as a forum for future collaborations.