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insurance_4

insurance_4

active ARFF Publicly available Visibility: public Uploaded 26-04-2023 by Pablo Torrijos Arenas
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  • bnlearn insurance Life Science Machine Learning sample
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Insurance Bayesian Network. Sample 4. bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#insurance) - Number of nodes: 27 - Number of arcs: 52 - Number of parameters: 1008 - Average Markov blanket size: 5.19 - Average degree: 3.85 - Maximum in-degree: 3 Authors: J. Binder, D. Koller, S. Russell, and K. Kanazawa Please cite: ([URL](https://cse.sc.edu/~mgv/csce582sp21/links/SDLC_CHILD_1993.pdf)): J. Binder, D. Koller, S. Russell, and K. Kanazawa. Adaptive Probabilistic Networks with Hidden Variables. Machine Learning, 29(2-3):213-244, 1997.

27 features

DrivHiststring3 unique values
0 missing
DrivingSkillstring3 unique values
0 missing
Agestring3 unique values
0 missing
RuggedAutostring3 unique values
0 missing
Mileagestring4 unique values
0 missing
VehicleYearstring2 unique values
0 missing
ILiCoststring4 unique values
0 missing
ThisCarDamstring4 unique values
0 missing
AntiTheftnominal2 unique values
0 missing
DrivQualitystring3 unique values
0 missing
RiskAversionstring4 unique values
0 missing
GoodStudentnominal2 unique values
0 missing
OtherCarnominal2 unique values
0 missing
MakeModelstring5 unique values
0 missing
Accidentstring4 unique values
0 missing
SocioEconstring4 unique values
0 missing
HomeBasestring4 unique values
0 missing
PropCoststring4 unique values
0 missing
CarValuestring5 unique values
0 missing
Antilocknominal2 unique values
0 missing
ThisCarCoststring3 unique values
0 missing
OtherCarCoststring3 unique values
0 missing
Theftnominal2 unique values
0 missing
Airbagnominal2 unique values
0 missing
MedCoststring4 unique values
0 missing
SeniorTrainnominal2 unique values
0 missing
Cushioningstring4 unique values
0 missing
Show all 27 features

19 properties

NumberOfInstances
5000
Number of instances (rows) of the dataset.
NumberOfFeatures
27
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
7
Number of nominal attributes.
PercentageOfNumericFeatures
0
Percentage of numeric attributes.
Dimensionality
0.01
Number of attributes divided by the number of instances.
PercentageOfSymbolicFeatures
25.93
Percentage of nominal attributes.
MajorityClassPercentage
Percentage of instances belonging to the most frequent class.
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
7
Number of binary attributes.
PercentageOfBinaryFeatures
25.93
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
PercentageOfMissingValues
0
Percentage of missing values.
AutoCorrelation
Average class difference between consecutive instances.
Show all 19 properties

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