Feature selection has become an important task for effective application of data mining techniquesin real-world high dimensional datasets. It is a process that selects a subset of original features by removing irrelevant and redundant features on the basis of the evaluation criteria without loss of information content. A feature selection method helps to reduce computational complexity of learn...

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...

-Classification, a data mining task is an effective method to classify the data in the process of Knowledge Data Discovery. Classification method algorithms are widely used in medical field to classify the medical data for diagnosis. Feature Selection increases the accuracy of the Classifier because it eliminates irrelevant attributes. This paper analyzes the performance of neural network class...

background: myocardial infarction (mi) occurs due to heart muscle death that costs like human life, which is higher than the treatment costs. this study aimed to present an mi prediction model using classification data mining methods, which consider the imbalance nature of the problem. methods: we enrolled 455 healthy and 295 myocardial infarction cases of visitors to shahid madani specialized ...

With the advancement of metagenome data mining science has become focused on microarrays. Microarrays are datasets with a large number of genes that are usually irrelevant to the output class; hence, the process of gene selection or feature selection is essential. So, it follows that you can remove redundant genes and increase the speed and accuracy of classification. After applying the gene se...

Genetic fuzzy rule selection is a two-phase classification rule mining method. First a large number of candidate fuzzy rules are generated by an association rule mining technique. Then only a small number of generated rules are selected by a genetic algorithm. We have already proposed an idea of parallel distributed implementation of genetic fuzzy rule selection. In this paper, we examine its c...

Educational data mining (EDM) is a new growing research area and the essence of data mining concepts are used in the educational field for the purpose of extracting useful information on the behaviors of students in the learning process. In this EDM, feature selection is to be made for the generation of subset of candidate variables. As the feature selection influences the predictive accuracy o...