This section describes main characteristics of the hepatitis data set and its attributes:
General information
Hepatitis data set |
Type | Classification | Origin | Real world |
Features | 19 | (Real / Integer / Nominal) | (2 / 17 / 0) |
Classes | 2 |
Missing values? | Yes |
Total instances | 155 |
Instances without missing values | 80 |
Attribute description
Attribute | Domain | Attribute | Domain |
Age | [7, 78] | Spiders | [1, 2] |
Sex | [1, 2] | Ascites | [1, 2] |
Steroid | [1, 2] | Varices | [1, 2] |
Antivirals | [1, 2] | Bilirubin | [0.3, 8.0] |
Fatigue | [1, 2] | AlkPhosphate | [26, 295] |
Malaise | [1, 2] | Sgot | [14, 648] |
Anorexia | [1, 2] | AlbuMin | [2.1, 6.4] |
LiverBig | [1, 2] | ProTime | [0, 100] |
LiverFirm | [1, 2] | Histology | [1, 2] |
SpleenPalpable | [1, 2] | Class | {1, 2} |
Additional information
This data set contains a mixture of integer and real valued attributes, with information about patients affected by the Hepatitis disease.
The task is to predict if these patients will die (1) or survive (2).
In this section you can download some files related to the hepatitis data set:
- The complete data set already formatted in KEEL formatcan 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/Hepatitis.
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