Publication Type : Conference Proceedings
Thematic Areas : Center for Computational Engineering and Networking (CEN)
Source : Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022), (834 - 839)
Campus : Coimbatore
School : School of Engineering
Department : Center for Computational Engineering and Networking (CEN)
Verified : No
Abstract : This paper narrates the work of the team Amrita_CEN for the shared task on Patronizing and Condescending Language Detection at SemEval 2022. We implemented machine learning algorithms such as Support Vector Machine (SVV), Logistic regression, Naive Bayes, XG Boost and Random Forest for modelling the tasks. At the same time, we also applied a feature engineering method to solve the class imbalance problem with respect to training data. Among all the models, the logistic regression model outperformed all other models and we have submitted results based upon the same.
Cite this Research Publication : George, Bichu and Adarsh, S and Prajapati, Nishitkumar and Premjith, B and Kp, Soman "Amrita_CEN at SemEval-2022 Task 4: Oversampling-based Machine Learning Approach for Detecting Patronizing and Condescending Language", Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)