This section describes main characteristics of the wisconsin data set and its attributes:
General information
Breast Cancer Wisconsin (Original) data set |
Type | Classification | Origin | Real world |
Features | 9 | (Real / Integer / Nominal) | (0 / 9 / 0) |
Classes | 2 |
Missing values? | Yes |
Total instances | 699 |
Instances without missing values | 683 |
Attribute description
Attribute | Domain |
ClumpThickness | [1, 10] |
CellSize | [1, 10] |
CellShape | [1, 10] |
MarginalAdhesion | [1, 10] |
EpithelialSize | [1, 10] |
BareNuclei | [1, 10] |
BlandChromatin | [1, 10] |
NormalNucleoli | [1, 10] |
Mitoses | [1, 10] |
Class | {2,4} |
Additional information
This dataset contains cases from a study that was conducted at the University of Wisconsin Hospitals, Madison, about patients who had undergone surgery for breast cancer. The task is to determine if the detected tumor is benign (2) os malignant (4).
To asses the data to classification process, the first attribute of the original data set (the sample code number) has been removed in this version.
In this section you can download some files related to the wisconsin 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/Breast+Cancer+Wisconsin+%28Original%29.
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