Accuracy for text classification

The classifier aglo is more or less un-changed since almost 10 years. I think a good reason for that could be, for example, NB, SVM have been able to achieve relatively high accuracy since long time back, provided with optimal/sub-optimal parameters.

While at the same time, a good approach to bump up the accuracy of overall text classification result is by data/corpus preparation, including stopwords, POS,TF-IDF etc, based on my experience.

Saw a good post on accuracy of text classification, echoing this:

6 Practices to enhance the performance of a Text Classification Model

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