Email Classification #79

[NeonKazuha]

• Tokenization: Split the text of each email into individual words or tokens.
  

• Normalization: Convert all text to lowercase, remove punctuation, and handle special cases (like email addresses or URLs).

• Stopword Removal: Remove common words that don't carry much meaning (e.g., "the", "is", "and").
  

• Feature Extraction: Represent each email as a numerical vector using techniques like bag-of-words, TF-IDF (Term Frequency-Inverse Document Frequency), or word embeddings.
  

Accuracy and Precision:

Precision Scores:

The best Precision score is given by Extra Trees Classifier: 0.9973

Solved Issue #79

Collab: https://colab.research.google.com/drive/1hlenQVeOThQZwZq6Hsr_VTI3v5soCBuV?usp=sharing