Ant colony optimization (ACO) algorithms have been applied successfully to combinatorial optimization problems. More recently, Parpinelli et al have applied ACO to data mining classification problems, where they introduced a classification algorithm called Ant Miner. In this paper, we present a system that combines both the proposed Improved Quickreduct algorithm for data preprocessing and ant ...

In most gene expression data, the number of training samples is very small compared to the large number of genes involved in the experiments. However, among the large amount of genes, only a small fraction is effective for performing a certain task. Furthermore, a small subset of genes is desirable in developing gene expression based diagnostic tools for delivering reliable and understandable r...

Attribute reduction of an information system is a key problem in rough set theory and its applications. Rough set theory has been one of the most successful methods used for feature selection. Rough set is one of the most useful data mining techniques. This paper proposes relative reduct to solve the attribute reduction problem in roughest theory. It is the most promising technique in the Rough...

Reduct finding, especially optimal reduct finding, similar to feature selection problem, is a crucial task in rough set applications to data mining, In this paper, we propose a heuristic reduct finding algorithm, which is based on frequencies of attributes appeared in discernibility matrix. Our method does not guarantee to find optimal reduct, but experiment shows that in most situations it doe...

he financial management field has witnessed significant developments in recent years to help decision makers, managers and investors, to made optimal decisions. In this regard, the institutions investment strategies and their evaluation methods continuously change with the rapid transfer of information and access to the fi- nancial data. When information is available ...

Lung cancer is the deadliest type of cancer for both men and women. Feature selection plays a vital role in cancer classification. This paper investigates the feature selection process in Computed Tomographic (CT) lung cancer images using soft set theory. We propose a new soft set based unsupervised feature selection algorithm. Nineteen features are extracted from the segmented lung images usin...

This paper proposes a reduct construction method based on discernibility matrix simplification. The method works in a similar way to the classical Gaussian elimination method for solving a system of linear equations. Elementary matrix simplification operations are introduced. Each operation transforms a matrix into a simpler form. By applying these operations a finite number of times, one can t...

In the present day huge amount of data is generated in every minute and transferred frequently. Although the data is sometimes static but most commonly it is dynamic and transactional. New data that is being generated is getting constantly added to the old/existing data. To discover the knowledge from this incremental data, one approach is to run the algorithm repeatedly for the modified data s...