This paper describes the systems submitted by our team for Indian Native Language Identification (INLI) task held in conjunction with FIRE 2017. Native Language Identification (NLI) is an important task that has different applications in different areas such as social-media analysis, authorship identification, second language acquisition and forensic investigation. We submitted two systems using Support Vector Machine (SVM) and Ensemble Classifier based on three different classifiers representing the comments (data) as vector space model for both systems and achieved accuracy of 47.60% and 47.30% respectively and secured second rank over all submissions for the task.