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Text Classification Using Gaussian, Multinomial naïve Bayes and Logistic Regression
Published Online: November-December 2022
Pages: 112-114
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No DOIAbstract
Text can be an extremely rich source of information, but extracting insights from it can be hard and time-consuming, due to its unstructured nature. It works by automatically analysing and structuring text, quickly and cost-effectively, so businesses can automate processes and discover insights that lead to better decision-making. The project is based on the text classification of a dataset which is relevant to the economics of the world and the US market. The project is based on predicting a particular statement based on the given query which shows the relevance of the statement to the economy. The model shows the statement is relevant to the economics.
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