Most rule induction algorithms generate rules with simple logical conditions based on
equality or inequality relations. This feature limits their ability to discover complex …

This article presents GuideR, a user-guided rule induction algorithm, which overcomes the
largest limitation of the existing methods—the lack of the possibility to introduce user's …

Rule-based models are often used for data analysis as they combine interpretability with
predictive power. We present RuleKit, a versatile tool for rule learning. Based on a …

Rule induction is a data mining technique used to extract classification rules of the form IF
(conditions) THEN (predicted class) from data. The majority of the rule induction algorithms …

RRULES is presented as an improvement and optimization over RULES, a simple inductive
learning algorithm for extracting IF-THEN rules from a set of training examples. RRULES …

Rule learning is one of the most popular areas in machine learning research, because the
outcome of learning is to produce a set of rules, which not only provides accurate predictions …

Due to the rapid growth of computer technologies and the extensive changes in human
needs, expertise and digital information were used to induce general conclusions. Such …

As data storage capacities continue to increase due to rapid advances in information
technology, there is a growing need for devising scalable data mining algorithms able to sift …

In every aspect of life, many information is flowing around in which human can take
advantage of. Thus, machine learning was born to gather such information and learn how it …

This paper presents the algorithm for induction of unordered sets of regression rules. It uses
sequential covering strategy and dynamic reduction to classification approach. The main …