Data
kidney

kidney

active ARFF Publicly available Visibility: public Uploaded 29-09-2014 by Joaquin Vanschoren
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Author: McGilchrist and Aisbett Source: [StatLib](http://lib.stat.cmu.edu/datasets/) - 1999 Please cite: Data on the recurrence times to infection, at the point of insertion of the catheter, for kidney patients using portable dialysis equipment. Catheters may be removed for reasons other than infection, in which case the observation is censored. Each patient has exactly 2 observations. The data set has been used by several authors to illustrate random effects ("frailty") models for survival data. However, any non-zero estimate of the random effect is almost entirely due to one outlier, subject 21. Variables: patient, time, status, age, sex (1=male, 2=female), disease type (0=Glomerulo Nephritis, 1=Acute Nephritis, 2=Polycystic Kidney Disease, 3=Other), author's estimate of the frailty References: McGilchrist and Aisbett, Biometrics 47, 461-66, 1991

7 features

frailty (target)numeric20 unique values
0 missing
patientnumeric38 unique values
0 missing
timenumeric60 unique values
0 missing
statusnominal2 unique values
0 missing
agenumeric30 unique values
0 missing
sexnominal2 unique values
0 missing
disease_typenominal4 unique values
0 missing

19 properties

76
Number of instances (rows) of the dataset.
7
Number of attributes (columns) of the dataset.
0
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.
4
Number of numeric attributes.
3
Number of nominal attributes.
57.14
Percentage of numeric attributes.
0.09
Number of attributes divided by the number of instances.
42.86
Percentage of nominal attributes.
Percentage of instances belonging to the most frequent class.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
2
Number of binary attributes.
28.57
Percentage of binary attributes.
0
Percentage of instances having missing values.
0
Percentage of missing values.
0.64
Average class difference between consecutive instances.

13 tasks

2 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: mean_absolute_error - target_feature: frailty
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: mean_absolute_error - target_feature: frailty
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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