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...

Feature extraction and feature selection are two important tasks in pattern recognition. Classiication algorithms like k-nearest neighbors, which are based on the assumption that patterns in the same class are close to each other and those in diierent classes are far apart (locality property), rely heavily on the quality of the features extracted from the input data. In this work, an objective ...

This chapter describes a method of feature selection and ranking based on human expert knowledge and training and testing of a neural network. Being computationally efficient, the method is less sensitive to round-off errors and noise in the data than the traditional methods of feature selection and ranking grounded on the sensitivity analysis. The method may lead to a significant reduction of ...