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This is a Multi Label Text Classification with implemented with python and ML. I first cleaned and pre-processed the texts, and then created a pipeline, which contained TfidfVectorizer. I used Multinomial Naive Bayes and Logistic Regression classifier. LR gave the best accuracy, averaging around 96%. This is a Kaggle competition problem.

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About

This is a Multi Label Text Classification with implemented with python and ML. I first cleaned and pre-processed the texts, and then created a pipeline, which contained TfidfVectorizer. I used Multinomial Naive Bayes and Logistic Regression classifier. LR gave the best accuracy, averaging around 96%. This is a Kaggle competition problem.

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3 stars

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1 watching

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