Sample Test Description: Spam Email Classification
- Dataset Name:
Email_Spam_Test_Set_v1.0
- Task Type: Binary Text Classification (
Spamvs.Not Spam)
- Total Sample Count: 1,000 instances (held out from the training set)
- Class Distribution:
- 300 Spam emails (30%)
- 700 Not Spam emails (70%)
- Input Feature Description: Raw text payload of the email message, including subject line and body text (UTF-8 encoded).
- Target / Ground Truth Label: Binary label (
1for Spam,0for Not Spam) hidden from the model during evaluation.
- Source & Collection Method: Aggregated from public enterprise support tickets and opted-in user reports between January 2026 and March 2026.
- Intended Evaluation Metrics:
- Precision
- Recall
- F1-Score
- False Positive Rate (FPR)
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