LSTM Based Text Classification
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Abstract
This paper will review the literature on various methods and algorithms for analysing text sentiment. This paper will go through different machine learning algorithms for detecting sentiment in a text. Many of the algorithms used here had drawbacks, such as taking longer to train the model and using small datasets to train, resulting in lower performance. The performance of the model was improved by using LSTM, and it took less time to train the model. When compared to LSTM, many other approaches, such as RNN and CNN, are inefficient. Various companies use Sentimental Analysis to better understand their customers’ reactions to their goods.
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