Using Grammar Based Genetic Programming for Data Mining of Medical Knowledge

Rule discovery in Web-based educational systems using Grammar-Based Genetic Programming

This paper describes the use of data mining methods in an e-learning system for providing feedback to courseware authors. The discovered information is presented in the form of prediction rules since these are highly comprehensible and they show important relationships among the presented data. The rules will be used to improve courseware, particularly Adaptive Systems for Web-based Education (...

Discovering knowledge from noisy databases using genetic programming

In data mining, we emphasize the need for learning from huge, incomplete and imperfect data sets (Fayyad et al. 1996, Frawley et al. 1991, Piatetsky-Shapiro and Frawley, 1991). To handle noise in the problem domain, existing learning systems avoid overfitting the imperfect training examples by excluding insignificant patterns. The problem is that these systems use a limiting attribute-value lan...

A Novel Method for Selecting the Supplier Based on Association Rule Mining

One of important problems in supply chains management is supplier selection. In a company, there are massive data from various departments so that extracting knowledge from the company’s data is too complicated. Many researchers have solved this problem by some methods like fuzzy set theory, goal programming, multi objective programming, the liner programming, mixed integer programming, analyti...

Data Mining Using Grammar Based Genetic Programming and Applications Genetic Programming Series

Applying Adaptive Grammar Based Genetic Programming in Evolving Recursive Programs

Genetic programming (GP) extends traditional genetic algorithms to automatically induce computer programs. GP has been applied in a wide range of applications such as software re-engineering, electrical circuits synthesis, knowledge engineering, and data mining. One of the most important and challenging research areas in GP is the investigation of ways to successfully evolve recursive programs....