aminul-huq/CNN-RNN-for-Multiclass-Classification-on-SST-dataset
PyTorch implementation of multi-class sentiment classification on SST dataset using CNN and RNN.
This helps researchers, linguists, or data scientists analyze the sentiment of text, categorizing it as positive, negative, or neutral. You input a collection of sentences or short texts, and it outputs the predicted emotional tone for each. This is useful for understanding public opinion, customer feedback, or literary analysis.
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Use this if you need to classify short text snippets into multiple sentiment categories (e.g., positive, negative, neutral) and want to experiment with different deep learning models.
Not ideal if you need to analyze the sentiment of very long documents, require fine-grained emotion detection beyond basic polarity, or are looking for an out-of-the-box solution without any coding.
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Apr 20, 2020
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