Detecting Hate Speech and Offensive Language on Twitter using Machine Learning: An N-gram and TFIDF based Approach
TABLE IV: Classification scores obtained after evaluating the final Logistic Regression model on test data.
['[EMPTY]', 'Precision', 'Recall', 'F-score']
Comparing the best accuracy for Naive Bayes and Logistic Regression, we conclude that Logistic Regression performs better. Therefore, we evaluate Logistic Regression on test data with the settings: n-gram range 1-3, TFIDF normalization L2, C=100 and optimization algorithm liblinear.