This paper deals with the problem of feature subset selection in classification-oriented datasets with a (very) large number of attributes. In such datasets complex classical wrapper approaches become intractable due to the high number of wrapper evaluations to be carried out. One way to alleviate this problem is to use the so-called filter-wrapper approach or Incremental Wrapper-based Subset S...

Autism spectrum disorder is a complex neurodevelopment that affects an individual's social behavior. Microarray analysis extensively used technique to detect autism. data can provide additional insight into the etiology of disorder. Identifying specific set genes associated with autism from microarray poses significant research challenge due its high dimensionality. However, Gene subset selecti...

Due to the rise of technology, the possibility of fraud in different areas such as banking has been increased. Credit card fraud is a crucial problem in banking and its danger is over increasing. This paper proposes an advanced data mining method, considering both feature selection and decision cost for accuracy enhancement of credit card fraud detection. After selecting the best and most effec...

In order to let software programs gain full benefit from semi-structured web sources, wrapper programs must be built to provide a “machine-readable” view over them. A significant problem in this approach arises as Web sources may undergo changes that invalidate the current wrappers. In this paper, we present novel heuristics and algorithms to address this problem. In our approach the system col...

A hybrid filter/wrapper feature subset selection algorithm for regression is proposed. First, features are filtered by means of a relevance and redundancy filter using mutual information between regression and target variables. We introduce permutation tests to find statistically significant relevant and redundant features. Second, a wrapper searches for good candidate feature subsets by taking...

Semi-automatic wrapper generation tools aim to ease the task of building structured views over semi-structured web sources. But the wrapper generation techniques presented up to date are unable to properly deal with sources requiring complex navigational sequences for accessing data. In this paper, we present Wargo, a semi-automatic wrapper generation tool, which has been used by non-programmer...

13 Selection of input features plays an important role in developing models for short14 term load forecasting (STLF). Previous studies along this line of research have focused 15 pre-dominantly on filter and wrapper methods. Given the potential value of a hybrid 16 selection scheme that includes both filter and wrapper methods in constructing an 17 appropriate pool of features, coupled with the...

This paper deals with the problem of supervised wrapper-based feature subset selection in datasets with a very large number of attributes. Recently the literature has contained numerous references to the use of hybrid selection algorithms: based on a filter ranking, they perform an incremental wrapper selection over that ranking. Though working fine, these methods still have their problems: (1)...