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--- |
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dataset_info: |
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features: |
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- name: content |
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dtype: string |
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- name: label |
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dtype: int64 |
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splits: |
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- name: train |
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num_bytes: 47241927 |
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num_examples: 120000 |
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- name: validation |
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num_bytes: 5052323 |
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num_examples: 20000 |
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- name: test |
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num_bytes: 14856442 |
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num_examples: 60000 |
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download_size: 40289388 |
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dataset_size: 67150692 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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- split: validation |
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path: data/validation-* |
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- split: test |
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path: data/test-* |
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--- |
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# Phishing Email Detection Dataset |
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A comprehensive dataset combining email messages and URLs for phishing detection. |
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## Dataset Overview |
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### Quick Facts |
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- **Task Type**: Multi-class Classification |
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- **Languages**: English |
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- **Total Samples**: 200,000 entries |
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- **Size Split**: |
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- Email samples: 22,644 |
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- URL samples: 177,356 |
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- **Label Distribution**: Four classes (0, 1, 2, 3) |
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- **Format**: Two columns - `content` and `labels` |
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## Dataset Structure |
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### Features |
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```python |
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{ |
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'content': Value(dtype='string', description='The text content - either email body or URL'), |
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'labels': ClassLabel(num_classes=4, names=[ |
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'legitimate_email', # 0 |
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'phishing_email', # 1 |
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'legitimate_url', # 2 |
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'phishing_url' # 3 |
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], description='Multi-class label for content classification') |
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} |