  Stylometry is the study of the unique linguistic styles and writing behaviors
of individuals. It belongs to the core task of text categorization like
authorship identification, plagiarism detection etc. Though reasonable number
of studies have been conducted in English language, no major work has been done
so far in Bengali. In this work, We will present a demonstration of authorship
identification of the documents written in Bengali. We adopt a set of
fine-grained stylistic features for the analysis of the text and use them to
develop two different models: statistical similarity model consisting of three
measures and their combination, and machine learning model with Decision Tree,
Neural Network and SVM. Experimental results show that SVM outperforms other
state-of-the-art methods after 10-fold cross validations. We also validate the
relative importance of each stylistic feature to show that some of them remain
consistently significant in every model used in this experiment.
