Data
hepar2_9

hepar2_9

active ARFF Publicly available Visibility: public Uploaded 26-04-2023 by Pablo Torrijos Arenas
0 likes downloaded by 0 people , 0 total downloads 0 issues 0 downvotes
  • bnlearn hepar2 Images Machine Learning sample
Issue #Downvotes for this reason By


Loading wiki
Help us complete this description Edit
Hepar2 Bayesian Network. Sample 9. bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-large.html#hepar2) - Number of nodes: 70 - Number of arcs: 123 - Number of parameters: 1453 - Average Markov blanket size: 4.51 - Average degree: 3.51 - Maximum in-degree: 6 Authors: A. Onisko. Please cite: ([URL](https://sites.pitt.edu/~druzdzel/psfiles/malbork.pdf)): A. Onisko. Probabilistic Causal Models in Medicine: Application to Diagnosis of Liver Disorders. Ph.D. Dissertation, Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Science, Warsaw, March 2003.

70 features

anorexiastring2 unique values
0 missing
triglyceridesstring3 unique values
0 missing
consciousnessstring2 unique values
0 missing
amylasestring3 unique values
0 missing
hepatotoxicstring2 unique values
0 missing
inrstring3 unique values
0 missing
jointsstring2 unique values
0 missing
plateletstring4 unique values
0 missing
vh_amnstring2 unique values
0 missing
spidersstring2 unique values
0 missing
spleenstring2 unique values
0 missing
agestring4 unique values
0 missing
jaundicestring2 unique values
0 missing
hbsag_antistring2 unique values
0 missing
ChHepatitisstring3 unique values
0 missing
itchingstring2 unique values
0 missing
Steatosisstring2 unique values
0 missing
sexstring2 unique values
0 missing
injectionsstring2 unique values
0 missing
hbsagstring2 unique values
0 missing
Cirrhosisstring3 unique values
0 missing
palmsstring2 unique values
0 missing
painstring2 unique values
0 missing
hcv_antistring2 unique values
0 missing
encephalopathystring2 unique values
0 missing
albuminstring3 unique values
0 missing
nauseastring2 unique values
0 missing
ureastring3 unique values
0 missing
phosphatasestring3 unique values
0 missing
RHepatitisstring2 unique values
0 missing
gallstonesstring2 unique values
0 missing
ggtpstring4 unique values
0 missing
PBCstring2 unique values
0 missing
altstring4 unique values
0 missing
bilirubinstring4 unique values
0 missing
fibrosisstring2 unique values
0 missing
aststring4 unique values
0 missing
hbeagstring2 unique values
0 missing
skinstring2 unique values
0 missing
pain_ruqstring2 unique values
0 missing
cholesterolstring3 unique values
0 missing
THepatitisstring2 unique values
0 missing
hbc_antistring2 unique values
0 missing
pressure_ruqstring2 unique values
0 missing
alcoholstring2 unique values
0 missing
le_cellsstring2 unique values
0 missing
amastring2 unique values
0 missing
ESRstring3 unique values
0 missing
hepatomegalystring2 unique values
0 missing
proteinsstring2 unique values
0 missing
hepatalgiastring2 unique values
0 missing
irregular_liverstring2 unique values
0 missing
ascitesstring2 unique values
0 missing
hospitalstring2 unique values
0 missing
obesitystring2 unique values
0 missing
diabetesstring2 unique values
0 missing
choledocholithotomystring2 unique values
0 missing
densitystring2 unique values
0 missing
transfusionstring2 unique values
0 missing
fatiguestring2 unique values
0 missing
flatulencestring2 unique values
0 missing
bleedingstring2 unique values
0 missing
upper_painstring2 unique values
0 missing
Hyperbilirubinemiastring2 unique values
0 missing
carcinomastring2 unique values
0 missing
edgestring2 unique values
0 missing
edemastring2 unique values
0 missing
fatstring2 unique values
0 missing
alcoholismstring2 unique values
0 missing
surgerystring2 unique values
0 missing

19 properties

5000
Number of instances (rows) of the dataset.
70
Number of attributes (columns) of the dataset.
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.
0
Number of numeric attributes.
0
Number of nominal attributes.
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.
0
Number of binary attributes.
0
Percentage of binary attributes.
0
Percentage of instances having missing values.
Average class difference between consecutive instances.
0
Percentage of missing values.
0.01
Number of attributes divided by the number of instances.
0
Percentage of numeric attributes.
Percentage of instances belonging to the most frequent class.
0
Percentage of nominal attributes.

0 tasks

Define a new task