Primary Tumor
Donated on 10/31/1988
From Ljubljana Oncology Institute
Dataset Characteristics
Multivariate
Subject Area
Health and Medicine
Associated Tasks
Classification
Feature Type
Categorical
# Instances
339
# Features
17
Dataset Information
Additional Information
This is one of three domains provided by the Oncology Institutenthat has repeatedly appeared in the machine learning literature. (See also breast-cancer and lymphography.)
Has Missing Values?
Yes
Variables Table
| Variable Name | Role | Type | Demographic | Description | Units | Missing Values |
|---|---|---|---|---|---|---|
| class | Target | Integer | no | |||
| age | Feature | Integer | Age | no | ||
| sex | Feature | Integer | Sex | yes | ||
| histologic-type | Feature | Integer | yes | |||
| degree-of-diffe | Feature | Integer | yes | |||
| bone | Feature | Integer | no | |||
| bone-marryow | Feature | Integer | no | |||
| lung | Feature | Integer | no | |||
| pleura | Feature | Integer | no | |||
| peritoneum | Feature | Integer | no |
0 to 10 of 18
Additional Variable Information
--- NOTE: All attribute values in the database have been entered as numeric values corresponding to their index in the list of attribute values for that attribute domain as given below. 1. class: lung, head & neck, esophasus, thyroid, stomach, duoden & sm.int, colon, rectum, anus, salivary glands, pancreas, gallblader, liver, kidney, bladder, testis, prostate, ovary, corpus uteri, cervix uteri, vagina, breast 2. age: <30, 30-59, >=60 3. sex: male, female 4. histologic-type: epidermoid, adeno, anaplastic 5. degree-of-diffe: well, fairly, poorly 6. bone: yes, no 7. bone-marrow: yes, no 8. lung: yes, no 9. pleura: yes, no 10. peritoneum: yes, no 11. liver: yes, no 12. brain: yes, no 13. skin: yes, no 14. neck: yes, no 15. supraclavicular: yes, no 16. axillar: yes, no 17. mediastinum: yes, no 18. abdominal: yes, no
Class Labels
[1-22]: lung, head & neck, esophasus, thyroid, stomach, duoden & sm.int, colon, rectum, anus, salivary glands, pancreas, gallblader, liver, kidney, bladder, testis, prostate, ovary, corpus uteri, cervix uteri, vagina, breast
Dataset Files
| File | Size |
|---|---|
| primary-tumor.data | 12.1 KB |
| primary-tumor.names | 3.6 KB |
| Index | 132 Bytes |
Reviews
There are no reviews for this dataset yet.
pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset primary_tumor = fetch_ucirepo(id=83) # data (as pandas dataframes) X = primary_tumor.data.features y = primary_tumor.data.targets # metadata print(primary_tumor.metadata) # variable information print(primary_tumor.variables)
Zwitter, M. & Soklic, M. (1987). Primary Tumor [Dataset]. UCI Machine Learning Repository. https://doi.org/10.24432/C5WK5Q.
Keywords
Creators
M. Zwitter
M. Soklic
DOI
License
This dataset is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.
This allows for the sharing and adaptation of the datasets for any purpose, provided that the appropriate credit is given.