Abstract
Suspicious Bangla text detection is a text classification problem of determining Bangla texts into suspicious and non suspicious categories. In this paper, we have proposed a machine learning based system that can classify Bangla texts into suspicious and non-suspicious. For this purpose, a corpus is developed and logistic regression algorithm is used for classification task. In order to measure the effectiveness of the proposed system a comparison of accuracy among other algorithms such as Naive Bayes, SVM, KNN, and decision tree also performed. The experimental result with 1500 training documents and 500 testing documents shows that the logistic regression provides the highest accuracy (92%) than other algorithms.
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Sharif, O., Hoque, M.M. (2020). Automatic Detection of Suspicious Bangla Text Using Logistic Regression. In: Vasant, P., Zelinka, I., Weber, GW. (eds) Intelligent Computing and Optimization. ICO 2019. Advances in Intelligent Systems and Computing, vol 1072. Springer, Cham. https://doi.org/10.1007/978-3-030-33585-4_57
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DOI: https://doi.org/10.1007/978-3-030-33585-4_57
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