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mildew_10

mildew_10

active ARFF Publicly available Visibility: public Uploaded 26-04-2023 by Pablo Torrijos Arenas
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  • bnlearn Machine Learning mildew sample Transportation
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Mildew Bayesian Network. Sample 10. bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#mildew) - Number of nodes: 35 - Number of arcs: 46 - Number of parameters: 540150 - Average Markov blanket size: 4.57 - Average degree: 2.63 - Maximum in-degree: 3 Authors: A. L. Jensen and F. V. Jensen. Please cite: ([URL](https://www.semanticscholar.org/paper/MIDAS%3A-An-Influence-Diagram-for-Management-of-in-Jensen-Jensen/a08ce2d88c66bb5bf7968bdadee87c2f91caeb2c)): A. L. Jensen and F. V. Jensen. MIDAS - An Influence Diagram for Management of Mildew in Winter Wheat. Proceedings of the Twelfth Conference on Uncertainty in Artificial Intelligence (UAI1996), pages 349-356.

35 features

mikro_2string4 unique values
0 missing
lai_1string8 unique values
0 missing
foto_2string18 unique values
0 missing
meldug_2string9 unique values
0 missing
straaling_1string4 unique values
0 missing
foto_3string28 unique values
0 missing
foto_4string18 unique values
0 missing
nedboer_2string3 unique values
0 missing
udbyttestring73 unique values
0 missing
mikro_3string4 unique values
0 missing
lai_3string7 unique values
0 missing
dm_3string75 unique values
0 missing
meldug_1string9 unique values
0 missing
meldug_4string9 unique values
0 missing
middel_2string4 unique values
0 missing
middel_1string4 unique values
0 missing
temp_4string4 unique values
0 missing
temp_1string4 unique values
0 missing
straaling_4string4 unique values
0 missing
temp_3string4 unique values
0 missing
lai_4string3 unique values
0 missing
straaling_3string4 unique values
0 missing
middel_3string4 unique values
0 missing
meldug_3string9 unique values
0 missing
straaling_2string4 unique values
0 missing
dm_1string29 unique values
0 missing
nedboer_1string3 unique values
0 missing
lai_2string8 unique values
0 missing
nedboer_3string3 unique values
0 missing
foto_1string19 unique values
0 missing
lai_0string6 unique values
0 missing
dm_4string86 unique values
0 missing
mikro_1string4 unique values
0 missing
temp_2string4 unique values
0 missing
dm_2string47 unique values
0 missing
Show all 35 features

19 properties

NumberOfInstances
5000
Number of instances (rows) of the dataset.
NumberOfFeatures
35
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.
PercentageOfBinaryFeatures
0
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
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.
Show all 19 properties

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