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This repo builds a text classification pipeline using scikit-learn. It applies feature extraction with CountVectorizer and TfidfVectorizer, and evaluates models like Logistic Regression, Decision Tree, Random Forest, SVM, and Naive Bayes. Key metrics used include accuracy and precision, with support from pandas, numpy, and matplotlib.
jash72/Spam_Mail_Analysis_and_Detection
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This repo builds a text classification pipeline using scikit-learn. It applies feature extraction with CountVectorizer and TfidfVectorizer, and evaluates models like Logistic Regression, Decision Tree, Random Forest, SVM, and Naive Bayes. Key metrics used include accuracy and precision, with support from pandas, numpy, and matplotlib.
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