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Using Naive Bayes and Logistic Regression filtering out spam and ham emails.
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Option 1: To execute, Run the algorithm.py file with arguments as below for each model and representation Multinomial Naive Bayes on Bag of words: python algorithm.py MULTINOMIALNB 1 python algorithm.py MULTINOMIALNB 2 python algorithm.py MULTINOMIALNB 3 Discrete Naive Bayes on Bernoulli's model: python algorithm.py DISCRETENB 1 python algorithm.py DISCRETENB 2 python algorithm.py DISCRETENB 3 Logistic Regression (Bag of words & Bernoulli): python algorithm.py LR 1 python algorithm.py LR 2 python algorithm.py LR 3 SGD Classifier (Bag of words & Bernoulli): python algorithm.py SGDClassifier 1 python algorithm.py SGDClassifier 2 python algorithm.py SGDClassifier 3 Option 2: To run in google colab, extract the colab_files.zip in colab 1. open notebook (algorithms.ipynb) 2. Load the Datasets.zip in the Files section of the colab 3. Run the notebook from starting Depending on which algorithm to use, comment and uncomment the strings in main function
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Using Naive Bayes and Logistic Regression filtering out spam and ham emails.
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