Data
thoracic-surgery

thoracic-surgery

active ARFF Publicly available Visibility: public Uploaded 25-05-2015 by Rafael Gomes Mantovani
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  • mf_less_than_80 study_123 study_127 study_50 study_52 study_7 study_88 study_236
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Author: Source: UCI Please cite: Zikeba, M., Tomczak, J. M., Lubicz, M., & Swikatek, J. (2013). Boosted SVM for extracting rules from imbalanced data in application to prediction of the post-operative life expectancy in the lung cancer patients. Applied Soft Computing. * Title: Thoracic Surgery Data Data Set * Abstract: The data is dedicated to classification problem related to the post-operative life expectancy in the lung cancer patients: class 1 - death within one year after surgery, class 2 - survival. * Source: Creators: Marek Lubicz (1), Konrad Pawelczyk (2), Adam Rzechonek (2), Jerzy Kolodziej (2) -- (1) Wroclaw University of Technology, wybrzeze Wyspianskiego 27, 50-370, Wroclaw, Poland -- (2) Wroclaw Medical University, wybrzeze L. Pasteura 1, 50-367 Wroclaw, Poland Donor: Maciej Zieba (maciej.zieba '@' pwr.wroc.pl), Jakub M. Tomczak (jakub.tomczak '@' pwr.wroc.pl), (+48) 71 320 44 53 * Data Set Information: The data was collected retrospectively at Wroclaw Thoracic Surgery Centre for patients who underwent major lung resections for primary lung cancer in the years 2007–2011. The Centre is associated with the Department of Thoracic Surgery of the Medical University of Wroclaw and Lower-Silesian Centre for Pulmonary Diseases, Poland, while the research database constitutes a part of the National Lung Cancer Registry, administered by the Institute of Tuberculosis and Pulmonary Diseases in Warsaw, Poland. * Attribute Information: 1. DGN: Diagnosis - specific combination of ICD-10 codes for primary and secondary as well multiple tumours if any (DGN3,DGN2,DGN4,DGN6,DGN5,DGN8,DGN1) 2. PRE4: Forced vital capacity - FVC (numeric) 3. PRE5: Volume that has been exhaled at the end of the first second of forced expiration - FEV1 (numeric) 4. PRE6: Performance status - Zubrod scale (PRZ2,PRZ1,PRZ0) 5. PRE7: Pain before surgery (T,F) 6. PRE8: Haemoptysis before surgery (T,F) 7. PRE9: Dyspnoea before surgery (T,F) 8. PRE10: Cough before surgery (T,F) 9. PRE11: Weakness before surgery (T,F) 10. PRE14: T in clinical TNM - size of the original tumour, from OC11 (smallest) to OC14 (largest) (OC11,OC14,OC12,OC13) 11. PRE17: Type 2 DM - diabetes mellitus (T,F) 12. PRE19: MI up to 6 months (T,F) 13. PRE25: PAD - peripheral arterial diseases (T,F) 14. PRE30: Smoking (T,F) 15. PRE32: Asthma (T,F) 16. AGE: Age at surgery (numeric) 17. Risk1Y: 1 year survival period - (T)rue value if died (T,F) Class Distribution: the class value (Risk1Y) is binary valued.

17 features

Class (target)nominal2 unique values
0 missing
V1nominal7 unique values
0 missing
V2numeric134 unique values
0 missing
V3numeric136 unique values
0 missing
V4nominal3 unique values
0 missing
V5nominal2 unique values
0 missing
V6nominal2 unique values
0 missing
V7nominal2 unique values
0 missing
V8nominal2 unique values
0 missing
V9nominal2 unique values
0 missing
V10nominal4 unique values
0 missing
V11nominal2 unique values
0 missing
V12nominal2 unique values
0 missing
V13nominal2 unique values
0 missing
V14nominal2 unique values
0 missing
V15nominal2 unique values
0 missing
V16numeric45 unique values
0 missing

19 properties

470
Number of instances (rows) of the dataset.
17
Number of attributes (columns) of the dataset.
2
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
3
Number of numeric attributes.
14
Number of nominal attributes.
64.71
Percentage of binary attributes.
0
Percentage of instances having missing values.
0.74
Average class difference between consecutive instances.
0
Percentage of missing values.
0.04
Number of attributes divided by the number of instances.
17.65
Percentage of numeric attributes.
85.11
Percentage of instances belonging to the most frequent class.
82.35
Percentage of nominal attributes.
400
Number of instances belonging to the most frequent class.
14.89
Percentage of instances belonging to the least frequent class.
70
Number of instances belonging to the least frequent class.
11
Number of binary attributes.

14 tasks

113 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: Class
32 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: Class
0 runs - estimation_procedure: 33% Holdout set - target_feature: Class
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
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