Abstract—an unsuitable representation will make the task of mining classification rules very hard for a traditional evolutionary algorithm (EA). But for a given dataset, it is difficult to decide which one is the best representation used in the mining progress. In this paper, we analyses the effects of different representations for a traditional EA and proposed a growing evolutionary algorithm which was robust for mining classification rules in different datasets. Experiments showed that the proposed algorithm is effective in dealing with problems of deception, linkage, epistasis and multimodality in the mining task. Index Terms-association rule; evolutionary algorithm; representation; I
Abstract: This chapter discusses the use of evolutionary algorithms, particularly genetic algorithms...
Abstract: This paper describes RAGA, a data mining system that combines evolutionary and symbolic ma...
Summary. In this chapter, we discuss the application of evolutionary multiob-jective optimization (E...
There has been a growing interest in data mining in several AI-related areas, including evolutionary...
Searching for patterns in large database is one of the major tasks in data mining. This can be achie...
Genetic algorithm is an important algorithm of association rule mining. However, there is some issue...
This PHD thesis deals with the evolutionary algorithms for mining frequent patterns and discovering ...
Data mining is an important process, with applications found in many business, science and industria...
Evolutionary Algorithms (EAs) are populationbased, stochastic search algorithms that mimic natural e...
Abstract. Data mining means to summarize information from large amounts of raw data. It is one of th...
Evolutionary algorithm (EA) is an umbrella term used to describe population-based stochastic direct ...
Abstract—The classification problem can be addressed by numerous techniques and algorithms which bel...
The process of discovering interesting and unexpected rules from large data sets is known as associa...
Association Rule Mining technique that attempt to unearthing interesting pattern or relationship bet...
Data Stream Mining is the process of extracting knowledge structures from continuous, rapid data rec...
Abstract: This chapter discusses the use of evolutionary algorithms, particularly genetic algorithms...
Abstract: This paper describes RAGA, a data mining system that combines evolutionary and symbolic ma...
Summary. In this chapter, we discuss the application of evolutionary multiob-jective optimization (E...
There has been a growing interest in data mining in several AI-related areas, including evolutionary...
Searching for patterns in large database is one of the major tasks in data mining. This can be achie...
Genetic algorithm is an important algorithm of association rule mining. However, there is some issue...
This PHD thesis deals with the evolutionary algorithms for mining frequent patterns and discovering ...
Data mining is an important process, with applications found in many business, science and industria...
Evolutionary Algorithms (EAs) are populationbased, stochastic search algorithms that mimic natural e...
Abstract. Data mining means to summarize information from large amounts of raw data. It is one of th...
Evolutionary algorithm (EA) is an umbrella term used to describe population-based stochastic direct ...
Abstract—The classification problem can be addressed by numerous techniques and algorithms which bel...
The process of discovering interesting and unexpected rules from large data sets is known as associa...
Association Rule Mining technique that attempt to unearthing interesting pattern or relationship bet...
Data Stream Mining is the process of extracting knowledge structures from continuous, rapid data rec...
Abstract: This chapter discusses the use of evolutionary algorithms, particularly genetic algorithms...
Abstract: This paper describes RAGA, a data mining system that combines evolutionary and symbolic ma...
Summary. In this chapter, we discuss the application of evolutionary multiob-jective optimization (E...