Comparison of Classical Machine Learning Approaches on Bangla Textual Emotion Analysis
Table 5: Results of K-NN Classifier for Different Feature Combinations (K=5).
['[ITALIC]  [BOLD] Feature', '[ITALIC]  [BOLD] Accuracy', '[ITALIC]  [BOLD] F1(macro)']
The results indicate that the best k-NN model uses the tf-idf unigram as a feature (accuracy = 0.479, F1-macro = 0.318).