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vanessaaleung · Nov 12, 2020 · 90cc672 · 90cc672
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 # Spam Email Detection
 _Create models to predict if an email message is spam or not_
+
+## Data Exploration
+- Percentage of spam in the data is 13.41%
+- Finding 1: Spam message tends to be longer
+- Finding 2: Spam message tends to have more digits
+- Finding 3: Spam message tends to have more non-word characters
+
+## Modeling
+1. CountVectorizer & Multinomial Naive Bayes Classifier
+2. TfidfVectorizer & Multinomial Naive Bayes Classifier
+3. TfidfVectorizer & Support Vector Classification + Length of Document
+4. TfidfVectorizer & Logistic Regression + Length of Document + # of digits per Document
+5. CountVectorizer & Logistic Regression + + Length of Document + # of digits per Document + # of Non-word Characters