Data
barley_9

barley_9

active ARFF Publicly available Visibility: public Uploaded 26-04-2023 by Pablo Torrijos Arenas
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  • barley bnlearn Life Science Machine Learning sample
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Barley Bayesian Network. Sample 9. bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#alarm) - Number of nodes: 48 - Number of arcs: 84 - Number of parameters: 114005 - Average Markov blanket size: 5.25 - Average degree: 3.5 - Maximum in-degree: 4 Authors: Kristian Kristensen , Ilse A. Rasmussen and others Preliminary model for barley developed under the project: "Production of beer from Danish malting barley grown without the use of pesticides" by Kristian Kristensen , Ilse A. Rasmussen and others.

48 features

tkvsstring9 unique values
0 missing
tkvstring7 unique values
0 missing
aks_m2string8 unique values
0 missing
udbstring9 unique values
0 missing
proteinstring8 unique values
0 missing
sortstring67 unique values
0 missing
srtsizestring7 unique values
0 missing
dgv1059string6 unique values
0 missing
nedbareastring3 unique values
0 missing
srtprotstring9 unique values
0 missing
ngodnnstring9 unique values
0 missing
dgv5980string6 unique values
0 missing
forfrugtstring5 unique values
0 missing
spndxstring2 unique values
0 missing
sorttkvstring9 unique values
0 missing
aks_vgtstring9 unique values
0 missing
s2225string3 unique values
0 missing
saamngstring10 unique values
0 missing
saatidstring5 unique values
0 missing
saakernstring7 unique values
0 missing
kommstring5 unique values
0 missing
exptgensstring6 unique values
0 missing
pesticidstring2 unique values
0 missing
noptstring6 unique values
0 missing
nminstring5 unique values
0 missing
aar_modstring11 unique values
0 missing
frspdagstring8 unique values
0 missing
ngodntstring8 unique values
0 missing
mod_nminstring6 unique values
0 missing
rokapstring7 unique values
0 missing
slt22string4 unique values
0 missing
jordinfstring9 unique values
0 missing
bgbygstring6 unique values
0 missing
jordnstring9 unique values
0 missing
nprotstring7 unique values
0 missing
jordtypestring9 unique values
0 missing
nplacstring3 unique values
0 missing
partigermstring9 unique values
0 missing
markgrmstring10 unique values
0 missing
ntilgstring10 unique values
0 missing
ksortstring5 unique values
0 missing
dg25string7 unique values
0 missing
ngtilgstring10 unique values
0 missing
antplntstring7 unique values
0 missing
keraksstring7 unique values
0 missing
potnminstring8 unique values
0 missing
s2528string7 unique values
0 missing
ngodnstring8 unique values
0 missing
Show all 48 features

19 properties

NumberOfInstances
5000
Number of instances (rows) of the dataset.
NumberOfFeatures
48
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
0
Number of nominal attributes.
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
0
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
0
Number of binary attributes.
PercentageOfBinaryFeatures
0
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
Show all 19 properties

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