Data
alarm_9

alarm_9

active ARFF Publicly available Visibility: public Uploaded 26-04-2023 by Pablo Torrijos Arenas
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  • alarm bnlearn Life Science Machine Learning sample
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Alarm Bayesian Network. Sample 9. bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#alarm) - Number of nodes: 37 - Number of arcs: 46 - Number of parameters: 509 - Average Markov blanket size: 3.51 - Average degree: 2.49 - Maximum in-degree: 4 Authors: I. A. Beinlich, H. J. Suermondt, R. M. Chavez, and G. F. Cooper Please cite: ([URL](https://doi.org/10.1007/978-3-642-93437-7_28)): I. A. Beinlich, H. J. Suermondt, R. M. Chavez, and G. F. Cooper. The ALARM Monitoring System: A Case Study with Two Probabilistic Inference Techniques for Belief Networks. In Proceedings of the 2nd European Conference on Artificial Intelligence in Medicine, pages 247-256. Springer-Verlag, 1989.

37 features

DISCONNECTnominal2 unique values
0 missing
INSUFFANESTHnominal2 unique values
0 missing
PAPstring3 unique values
0 missing
HISTORYnominal2 unique values
0 missing
ARTCO2string3 unique values
0 missing
ERRCAUTERnominal2 unique values
0 missing
HRBPstring3 unique values
0 missing
PRESSstring4 unique values
0 missing
FIO2string2 unique values
0 missing
BPstring3 unique values
0 missing
VENTMACHstring4 unique values
0 missing
VENTTUBEstring4 unique values
0 missing
CATECHOLstring2 unique values
0 missing
COstring3 unique values
0 missing
INTUBATIONstring3 unique values
0 missing
ERRLOWOUTPUTnominal2 unique values
0 missing
PCWPstring3 unique values
0 missing
MINVOLSETstring3 unique values
0 missing
TPRstring3 unique values
0 missing
CVPstring3 unique values
0 missing
VENTLUNGstring4 unique values
0 missing
ANAPHYLAXISnominal2 unique values
0 missing
PVSATstring3 unique values
0 missing
MINVOLstring4 unique values
0 missing
EXPCO2string4 unique values
0 missing
HRSATstring3 unique values
0 missing
LVFAILUREnominal2 unique values
0 missing
HYPOVOLEMIAnominal2 unique values
0 missing
HREKGstring3 unique values
0 missing
LVEDVOLUMEstring3 unique values
0 missing
SAO2string3 unique values
0 missing
PULMEMBOLUSnominal2 unique values
0 missing
HRstring3 unique values
0 missing
VENTALVstring4 unique values
0 missing
STROKEVOLUMEstring3 unique values
0 missing
KINKEDTUBEnominal2 unique values
0 missing
SHUNTstring2 unique values
0 missing
Show all 37 features

19 properties

NumberOfInstances
5000
Number of instances (rows) of the dataset.
NumberOfFeatures
37
Number of attributes (columns) of the dataset.
NumberOfClasses
Number of distinct values of the target attribute (if it is nominal).
NumberOfMissingValues
0
Number of missing values in the dataset.
NumberOfInstancesWithMissingValues
0
Number of instances with at least one value missing.
NumberOfNumericFeatures
0
Number of numeric attributes.
NumberOfSymbolicFeatures
10
Number of nominal attributes.
PercentageOfBinaryFeatures
27.03
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
AutoCorrelation
Average class difference between consecutive instances.
PercentageOfMissingValues
0
Percentage of missing values.
Dimensionality
0.01
Number of attributes divided by the number of instances.
PercentageOfNumericFeatures
0
Percentage of numeric attributes.
MajorityClassPercentage
Percentage of instances belonging to the most frequent class.
PercentageOfSymbolicFeatures
27.03
Percentage of nominal attributes.
MajorityClassSize
Number of instances belonging to the most frequent class.
MinorityClassPercentage
Percentage of instances belonging to the least frequent class.
MinorityClassSize
Number of instances belonging to the least frequent class.
NumberOfBinaryFeatures
10
Number of binary attributes.
Show all 19 properties

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