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