ksdkamesh99/Spam-Classifier
A Natural Language Processing with SMS Data to predict whether the SMS is Spam/Ham with various ML Algorithms like multinomial-naive-bayes,logistic regression,svm,decision trees to compare accuracy and using various data cleaning and processing techniques like PorterStemmer,CountVectorizer,TFIDF Vetorizer,WordnetLemmatizer. It is implemented using LSTM and Word Embeddings to gain accuracy of 97.84%.
This project helps anyone dealing with unwanted text messages by automatically identifying them as either legitimate ('ham') or spam. You provide a collection of text messages, and it classifies each one, helping you filter out junk. This tool is for individuals or businesses who need to manage or clean SMS communication logs.
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Use this if you need to reliably categorize a large volume of SMS messages to distinguish between genuine communication and unsolicited spam.
Not ideal if you are looking to classify other forms of text, like emails or social media posts, as it is specifically trained for SMS data.
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Jupyter Notebook
License
MIT
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Last pushed
Dec 25, 2020
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