  Authorship attribution, being an important problem in many areas in-cluding
information retrieval, computational linguistics, law and journalism etc., has
been identified as a subject of increasingly research interest in the re-cent
years. In case of Author Identification task in PAN at CLEF 2015, the main
focus was given on cross-genre and cross-topic author verification tasks. We
have used several word-based and style-based features to identify the
dif-ferences between the known and unknown problems of one given set and label
the unknown ones accordingly using a Random Forest based classifier.
