An Algorithm Evaluation for Discovering Classification Rules with Gene Expression Programming
نویسندگان
چکیده
منابع مشابه
Discovering interesting classification rules with genetic programming
Data mining deals with the problem of discovering novel and interesting knowledge from large amount of data. This problem is often performed heuristically when the extraction of patterns is difficult using standard query mechanisms or classical statistical methods. In this paper a genetic programming framework, capable of performing an automatic discovery of classification rules easily comprehe...
متن کاملEvolving accurate and compact classification rules with gene expression programming
Classification is one of the fundamental tasks of data mining. Most rule induction and decision tree algorithms perform local, greedy search to generate classification rules that are often more complex than necessary. Evolutionary algorithms for pattern classification have recently received increased attention because they can perform global searches. In this paper, we propose a new approach fo...
متن کاملDiscovering Fuzzy Classification Rules with Genetic Programming and Co-evolution
In essence, data mining consists of extracting knowledge from data. This paper proposes a co-evolutionary system for discovering fuzzy classification rules. The system uses two evolutionary algorithms: a genetic programming (GP) algorithm evolving a population of fuzzy rule sets and a simple evolutionary algorithm evolving a population of membership function definitions. The two populations co-...
متن کاملA Genetic Algorithm for Discovering Classification Rules in Data Mining
Data mining has as goal to discover knowledge from huge volume of data. Rule mining is considered as one of the usable mining method in order to obtain valuable knowledge from stored data on database systems. In this paper, a genetic algorithm-based approach for mining classification rules from large database is presented. For emphasizing on accuracy, coverage and comprehensibility of the rules...
متن کاملDiscovering Accurate and Interesting Classification Rules Using Genetic Algorithm
Discovering accurate and interesting classification rules is a significant task in the post-processing stage of a data mining (DM) process. Therefore, an optimization problem exists between the accuracy and the interesting metrics for post-processing rule sets. To achieve a balance, in this paper, we propose two major post-processing tasks. In the first task, we use a genetic algorithm (GA) to ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Computational Intelligence Systems
سال: 2016
ISSN: 1875-6891,1875-6883
DOI: 10.1080/18756891.2016.1150000