The performance in higher secondary school education in India is a turning point in the academic lives of all students. As this academic performance is influenced by many factors, it is essential to develop predictive data mining model for students’ performance so as to identify the slow learners and study the influence of the dominant factors on their academic performance. In the present inves...

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...

The typical data mining process is characterized by the prospective and iterative application of a variety of different data mining algorithms from an algorithm toolbox. While it would be desirable to check many different algorithms and algorithm combinations for their performance on a database, it is often not feasible because of time and other resource constraints. This paper investigates the...

Breast cancer has become a widespread disease around the world in young women. Expert systems, developed by data mining techniques, are valuable tools in diagnosis of breast cancer and can help physicians for decision making process. This paper presents a new hybrid data mining approach to classify two groups of breast cancer patients (malignant and benign). The proposed approach, AP-AMBFA, con...

Abstract— Feature selection is a term commonly used in data mining to describe the tools and techniques available for reducing inputs to a manageable size for processing and analysis. Feature selection implies not only cardinality reduction, which means imposing an arbitrary or predefined cutoff on the number of attributes that can be considered when building a model, but also the choice of att...

Feature selection is a pre-processing step, used to improve the mining performance by reducing data dimensionality. Even though there exists a number of feature selection algorithms, still it is an active research area in data mining, machine learning and pattern recognition communities. Many feature selection algorithms confront severe challenges in terms of effectiveness and efficiency, becau...

Background: The clinical field has vast sick data that has not been analyzed. Discovering a way to analyze this raw data and turn it into an information treasure can save many lives. Using data mining methods is an efficient way to analyze this large amount of raw data. It can predict the future with accurate knowledge of the past, providing new insights into disease diagnosis and prevention. S...

one of the most important steps involved in mining operations is to select an appropriate extraction method for mine resources. after choosing the extraction method, it is usually impossible to replace it with another one because it may be so expensive that implementation of the entire project could be economically impossible. choosing a mining method depends on the geological and geometrical c...