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In this project, concepts of Natural Language Processing were used with the help of various Classification algorithms. The output will be classified as Spam or Ham.

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therahulparmar/SMS-Spam-Classification

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sms-spam-classification

In this project various classifiers are been used followed by accuracy,
They are:-
(1) Logistic Regression: 95.33%

(2) Multinomial Naive Bayes: 97.60%

(3) Decision Tree Classifier: 95.81%

(4) Support Vector Machine: 97.12%

(5) Random FOrest Classifier: 97.54%

The output will be classified as a Spam or Ham.

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In this project, concepts of Natural Language Processing were used with the help of various Classification algorithms. The output will be classified as Spam or Ham.

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