30lm32/ml-spam-sms-classification

Naive Bayesian, SVM, Random Forest Classifier, and Deeplearing (LSTM) on top of Keras and wod2vec TF-IDF were used respectively in SMS classification

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This project helps anyone dealing with a large volume of incoming SMS messages automatically identify and filter out spam. By feeding in raw SMS text, it determines if a message is 'spam' or 'ham' (not spam). This is useful for mobile carriers, customer support teams, or anyone managing SMS communications.

No commits in the last 6 months.

Use this if you need to automatically detect and classify unwanted promotional or phishing SMS messages from legitimate ones.

Not ideal if your primary need is to classify text messages based on sentiment, topic, or other content beyond just 'spam' or 'not spam'.

SMS filtering spam detection telecommunications customer communication text message management

No License Stale 6m No Package No Dependents

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Maturity 8 / 25

Community 19 / 25

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