Datasets:
| { | |
| "READY": true, | |
| "name": "thyroid", | |
| "task": "classification", | |
| "num_classes": 3, | |
| "cat_idx": [ | |
| 1, | |
| 2, | |
| 3, | |
| 4, | |
| 5, | |
| 6, | |
| 7, | |
| 8, | |
| 9, | |
| 10, | |
| 11, | |
| 12, | |
| 13, | |
| 14 | |
| ], | |
| "num_samples": 7200, | |
| "num_features": 20, | |
| "imbalance_ratio": 40.1566, | |
| "description": "Three-class UCI ANN thyroid task in TALENT row order. Released UCI feature values are restored before TALENT per-source-file z-scoring; the 15 binary flags are categorical. Standard preprocessing removes hypopituitary, constant in training, leaving 20 features (14 categorical). Labels and the stored TabBioMed 70/15/15 split are preserved. Any model scaling is fitted on its training partition.", | |
| "source": "Talent Benchmark Dataset - thyroid", | |
| "label": "clinical & healthcare", | |
| "curation_protocol": "clinical_source_coding_v1" | |
| } | |