📩 Advanced Email Spam Classifier

Enter the content of an email below to classify it as Spam or Ham.

The tool uses machine learning to analyze email content, highlights spammy keywords, and shows key performance analytics.

📊 Model Performance Analytics

🛠️ Save and Retrain the Model

📘 Glossary and Explanation of Labels

Labels:

• Spam: Unwanted or harmful emails flagged by the system.
• Ham: Legitimate, safe emails.

Confusion Matrix:

The confusion matrix shows the performance of the model by comparing the true labels with the predicted ones. It consists of:

• True Positives (TP): Correctly predicted spam emails.
• True Negatives (TN): Correctly predicted ham emails.
• False Positives (FP): Ham emails incorrectly predicted as spam.
• False Negatives (FN): Spam emails incorrectly predicted as ham.

Metrics:

• Accuracy: The percentage of correct classifications.
• Precision: Out of predicted Spam, how many are actually Spam.
• Recall: Out of all actual Spam emails, how many are predicted as Spam.
• F1 Score: Harmonic mean of Precision and Recall.