This section describes main characteristics of the newthyroid data set and its attributes:
General information
| Thyroid Disease (New Thyroid) data set |
| Type | Classification | Origin | Real world |
| Features | 5 | (Real / Integer / Nominal) | (4 / 1 / 0) |
| Instances | 215 |
Classes | 3 |
| Missing values? | No |
Attribute description
| Attribute | Domain |
| T3resin | [65, 144] |
| Thyroxin | [0.5, 25.3] |
| Triiodothyronine | [0.2, 10.0] |
| Thyroidstimulating | [0.1, 56.4] |
| TSH_value | [-0.7, 56.3] |
| Class | {3, 2, 1} |
Additional information
This data set is one of the several databases about Thyroid avalaible at the UCI repository. The task is to detect is a given patient is normal (1) or suffers from hyperthyroidism (2) or hypothyroidism (3)
In this section you can download some files related to the newthyroid data set:
- The complete data set already formatted in KEEL format can be downloaded from
here
.
- A copy of the data set already partitioned by means of a 10-folds cross validation procedure can be downloaded from here
.
- A copy of the data set already partitioned by means of a 5-folds cross validation procedure can be downloaded from here
.
- The header file associated to this data set can be downloaded from here
.
- This is not a native data set from the KEEL project. It has been obtained from the UCI Machine Learning Repository . The original page where the data set can be found is: http://archive.ics.uci.edu/ml/datasets/Thyroid+Disease.
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