Spam Classifier - Step 9 - Evaluate the Model

1 Spam Classifier - Step 1- Get the SpamAssassin Dataset from their Website

2 Spam Classifier - About the Spam Dataset

3 Spam Classifier - Fetch the Dataset

4 Spam Classifier - Call the Function

5 Spam Classifier - Load all Emails

6 Spam Classifier - Step 2 - Parse the Emails

7 Spam Classifier - Parse the Emails

8 Spam Classifier - Step 3 - Explore the Emails

9 Spam Classifier - Check Content of Emails

10 Spam Classifier - Looking at Type of Email Structures

11 Spam Classifier - Most plain text emails

12 Spam Classifier - Most HTML emails

13 Spam Classifier - Step 4 - Preprocess the Data

14 Spam Classifier - Split the Dataset

15 Spam Classifier - Create a Preprocessing Function

16 Spam Classifier - Test HTML to Plain Text Function

17 Spam Classifier - Step 5 - Create Word Counts from Emails

18 Spam Classifier - Create Transformer to Convert Emails to Word Counters

19 Spam Classifier - Try the Transformer on few Emails

20 Spam Classifier - Step 6 - Convert Word Counts to Vectors

21 Spam Classifier - Create Transformer to Convert Word Counts to Vectors

22 Spam Classifier - Step 7 - Create Processing Pipeline

23 Spam Classifier - Create a Pipeline to Transform the Entire Dataset

24 Spam Classifier - Step 8 - Create Logistic Regression Model

25 Spam Classifier - Train a LogisticRegression model on the Dataset

26 Spam Classifier - Step 9 - Evaluate the Model

27 Spam Classifier - Calculate the Precision and Recall for the model