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We upload our dataset first, then perform preprocessing such as stemming and removing stop words, before applying our machine learning models and calculating accuracy for each model. Finally, the most accurate model is chosen. The best model is then used to estimate toxicity based on unknown data. Scikit-Learn is a free Python machine learning library. Supports both controlled and uncontrolled machine learning and includes a number of algorithms for classification, regression, grouping, and size reduction. This library was created using many libraries you know, such as NumPy and SciPy. It can also be used with other libraries, such as Panda and Seaborn.

Figure 9 We upload our dataset first, then perform preprocessing such as stemming and removing stop words, before applying our machine learning models and calculating accuracy for each model. Finally, the most accurate model is chosen. The best model is then used to estimate toxicity based on unknown data. Scikit-Learn is a free Python machine learning library. Supports both controlled and uncontrolled machine learning and includes a number of algorithms for classification, regression, grouping, and size reduction. This library was created using many libraries you know, such as NumPy and SciPy. It can also be used with other libraries, such as Panda and Seaborn.

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