It is a general, cheap way of incorporating prior probabilistic knowledge in arbitrary form into Data Mining algorithms addressing supervised learning tasks.

An extension of subgroup discovery by the knowledge-based sampling approach to iterative model refinement is presented, a general, ...

Abstract. Subgroup discovery aims at finding interesting subsets of a classified example set that deviates from the overall distribution. The.

It is a general, cheap way of incorporating prior probabilistic knowledge in arbitrary form into Data Mining algorithms addressing supervised learning tasks.

Subgroup discovery aims at finding interesting subsets of a classified example set that deviates from the overall distribution.

Jul 31, 2023 · Abstract. Pattern discovery is a machine learning technique that aims to find sets of items, subsequences, or substructures that are present ...

Subgroup discovery is a data mining technique which extracts interesting rules with respect to a target variable. An important characteristic of this task ...

Abstract. Subgroup discovery is a popular form of supervised rule learn- ing, applicable to descriptive and predictive tasks. In this work we study.

There are a number of Subgroup Discovery methods; for a survey that unifies ... In Data Mining and Knowledge Discovery Approaches Based on. Rule Induction ...

Sep 5, 2019 · We have developed a novel subgroup discovery method which employs a deep exploratory mining process to slice and dice thousands of potential subpopulations and ...