Rough Set-Based Analysis of Characteristic Features for ANN Classifier

Selection of characteristic features for a classification task is always crucial to high recognition ratio, regardlessly of the particular processing technique applied. Most methodologies offer some inherent mechanisms of dimension reduction that lead to expression of available data in more succinct way, however, combining elements of distinctively different approaches to data analysis brings interesting conclusions as to the role of particular features and their influence on the power of the resulting classifier. The paper presents research on such fusion of processing techniques, namely employing rough set based analysis of features for ANN classifier within stylometric studies on writing styles.