Statistical testing based feature selection for Native Language Identification INLI@FIRE2018

The proposed method is composed of a feature selection procedure and a two-step classification strategy, both based on a specific mass function construction method inspired by

The system developed by the LAST for the PAN@FIRE 2020 Task on Authorship Identification of SOurce COde (AI-SOCO) was aimed at obtaining the best possible performance by combining a

We have devised a machine learning-based voted classifier tool based on emotion feature and term frequency-inverse doc- ument frequency (tf-idf) features of an Arabic tweet.. For

Bharathi et.al .”Statistical testing based feature selection for Native Language Iden- tification”,In Working notes of FIRE 2018 - Forum for Information Retrieval

In this paper, we propose to use Hyperdimensional Computing (HDC) as supervised learning for identifying Indian Native Languages from the user’s social media comments written

Keywords: Artificial Neural Network · Ensemble Learning · Native Language Identification..

We have ex- tracted TF-IDF feature vectors from the given document and used SVM classifier to identify the native language of the document given by shared task on Indian Native

MCS cannot assure the improvement of the classification accuracy in general. Large diversity is a necessary condition for improving the classification performance. Using different