Data
cnae-9

cnae-9

active ARFF Publicly available Visibility: public Uploaded 24-06-2019 by Julia Moosbauer
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Author: Source: Unknown - Date unknown Please cite: Binarized version of the cnae-9 dataset (see version 1). Only instances with class labels 1 and 2 from the original dataset are considered.

857 features

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0 missing
V194numeric2 unique values
0 missing
V450numeric2 unique values
0 missing
V706numeric1 unique values
0 missing
V195numeric3 unique values
0 missing
V451numeric1 unique values
0 missing
V707numeric1 unique values
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V196numeric1 unique values
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V452numeric1 unique values
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V708numeric2 unique values
0 missing
V197numeric2 unique values
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V453numeric1 unique values
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V709numeric2 unique values
0 missing
V198numeric1 unique values
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V454numeric1 unique values
0 missing
V710numeric1 unique values
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V199numeric2 unique values
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V455numeric1 unique values
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V711numeric1 unique values
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V200numeric2 unique values
0 missing
V456numeric1 unique values
0 missing
V712numeric2 unique values
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V201numeric2 unique values
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V457numeric1 unique values
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V713numeric1 unique values
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V202numeric2 unique values
0 missing
V458numeric1 unique values
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V714numeric2 unique values
0 missing
V203numeric1 unique values
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V459numeric1 unique values
0 missing
V715numeric1 unique values
0 missing
V204numeric1 unique values
0 missing
V460numeric1 unique values
0 missing
V716numeric1 unique values
0 missing
V205numeric1 unique values
0 missing
V461numeric1 unique values
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V717numeric1 unique values
0 missing
V206numeric2 unique values
0 missing
V462numeric1 unique values
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V718numeric1 unique values
0 missing
V207numeric2 unique values
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V463numeric1 unique values
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V719numeric1 unique values
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V208numeric2 unique values
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V464numeric1 unique values
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V720numeric1 unique values
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V209numeric2 unique values
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V465numeric2 unique values
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V721numeric2 unique values
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V210numeric1 unique values
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V466numeric1 unique values
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V722numeric1 unique values
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V211numeric1 unique values
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V467numeric2 unique values
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V723numeric2 unique values
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V212numeric1 unique values
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V468numeric1 unique values
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V724numeric2 unique values
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V213numeric2 unique values
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V469numeric1 unique values
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V725numeric2 unique values
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V214numeric2 unique values
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V470numeric2 unique values
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V726numeric3 unique values
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V727numeric1 unique values
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V730numeric1 unique values
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V475numeric1 unique values
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V731numeric3 unique values
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V220numeric1 unique values
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V476numeric2 unique values
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V732numeric2 unique values
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V221numeric1 unique values
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V477numeric2 unique values
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V733numeric1 unique values
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V734numeric1 unique values
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V737numeric1 unique values
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V228numeric1 unique values
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V484numeric1 unique values
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V740numeric2 unique values
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V485numeric1 unique values
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V230numeric3 unique values
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V744numeric1 unique values
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V233numeric1 unique values
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V489numeric2 unique values
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V745numeric1 unique values
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V234numeric1 unique values
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V490numeric2 unique values
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V492numeric2 unique values
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V240numeric1 unique values
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V498numeric1 unique values
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V755numeric2 unique values
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V244numeric2 unique values
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V500numeric2 unique values
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V502numeric1 unique values
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V503numeric1 unique values
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V504numeric1 unique values
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V760numeric1 unique values
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V505numeric1 unique values
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V761numeric2 unique values
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V250numeric1 unique values
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V506numeric1 unique values
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V762numeric2 unique values
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V251numeric1 unique values
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V507numeric1 unique values
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V763numeric2 unique values
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V252numeric1 unique values
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V508numeric1 unique values
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V764numeric2 unique values
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V253numeric1 unique values
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V509numeric1 unique values
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V765numeric1 unique values
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V254numeric1 unique values
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V510numeric2 unique values
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V766numeric1 unique values
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V255numeric1 unique values
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V511numeric2 unique values
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V767numeric2 unique values
0 missing
V256numeric2 unique values
0 missing
V512numeric1 unique values
0 missing
V768numeric2 unique values
0 missing
Show first 100 features

62 properties

NumberOfInstances
240
Number of instances (rows) of the dataset.
NumberOfFeatures
857
Number of attributes (columns) of the dataset.
NumberOfClasses
2
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
856
Number of numeric attributes.
NumberOfSymbolicFeatures
1
Number of nominal attributes.
ClassEntropy
1
Entropy of the target attribute values.
MeanNoiseToSignalRatio
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
Quartile2AttributeEntropy
Second quartile (Median) of entropy among attributes.
Dimensionality
3.57
Number of attributes divided by the number of instances.
MeanNominalAttDistinctValues
2
Average number of distinct values among the attributes of the nominal type.
Quartile2KurtosisOfNumericAtts
240
Second quartile (Median) of kurtosis among attributes of the numeric type.
EquivalentNumberOfAtts
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
MeanSkewnessOfNumericAtts
11.46
Mean skewness among attributes of the numeric type.
Quartile2MeansOfNumericAtts
0
Second quartile (Median) of means among attributes of the numeric type.
MajorityClassPercentage
50
Percentage of instances belonging to the most frequent class.
MeanStdDevOfNumericAtts
0.04
Mean standard deviation of attributes of the numeric type.
Quartile2MutualInformation
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
MajorityClassSize
120
Number of instances belonging to the most frequent class.
MinAttributeEntropy
Minimal entropy among attributes.
Quartile2SkewnessOfNumericAtts
15.49
Second quartile (Median) of skewness among attributes of the numeric type.
MaxAttributeEntropy
Maximum entropy among attributes.
MinKurtosisOfNumericAtts
-1.56
Minimum kurtosis among attributes of the numeric type.
PercentageOfBinaryFeatures
0.12
Percentage of binary attributes.
Quartile2StdDevOfNumericAtts
0
Second quartile (Median) of standard deviation of attributes of the numeric type.
MaxKurtosisOfNumericAtts
240
Maximum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
0
Minimum of means among attributes of the numeric type.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
Quartile3AttributeEntropy
Third quartile of entropy among attributes.
MaxMeansOfNumericAtts
0.37
Maximum of means among attributes of the numeric type.
MinMutualInformation
Minimal mutual information between the nominal attributes and the target attribute.
PercentageOfMissingValues
0
Percentage of missing values.
Quartile3KurtosisOfNumericAtts
240
Third quartile of kurtosis among attributes of the numeric type.
MaxMutualInformation
Maximum mutual information between the nominal attributes and the target attribute.
MinNominalAttDistinctValues
2
The minimal number of distinct values among attributes of the nominal type.
PercentageOfNumericFeatures
99.88
Percentage of numeric attributes.
Quartile3MeansOfNumericAtts
0
Third quartile of means among attributes of the numeric type.
MaxNominalAttDistinctValues
2
The maximum number of distinct values among attributes of the nominal type.
MinSkewnessOfNumericAtts
0.67
Minimum skewness among attributes of the numeric type.
PercentageOfSymbolicFeatures
0.12
Percentage of nominal attributes.
Quartile3MutualInformation
Third quartile of mutual information between the nominal attributes and the target attribute.
MaxSkewnessOfNumericAtts
15.49
Maximum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
0
Minimum standard deviation of attributes of the numeric type.
Quartile1AttributeEntropy
First quartile of entropy among attributes.
Quartile3SkewnessOfNumericAtts
15.49
Third quartile of skewness among attributes of the numeric type.
MaxStdDevOfNumericAtts
0.55
Maximum standard deviation of attributes of the numeric type.
MinorityClassPercentage
50
Percentage of instances belonging to the least frequent class.
Quartile1KurtosisOfNumericAtts
56.21
First quartile of kurtosis among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
0.06
Third quartile of standard deviation of attributes of the numeric type.
MeanAttributeEntropy
Average entropy of the attributes.
MinorityClassSize
120
Number of instances belonging to the least frequent class.
Quartile1MeansOfNumericAtts
0
First quartile of means among attributes of the numeric type.
StdvNominalAttDistinctValues
0
Standard deviation of the number of distinct values among attributes of the nominal type.
MeanKurtosisOfNumericAtts
152.24
Mean kurtosis among attributes of the numeric type.
NumberOfBinaryFeatures
1
Number of binary attributes.
Quartile1MutualInformation
First quartile of mutual information between the nominal attributes and the target attribute.
MeanMeansOfNumericAtts
0.01
Mean of means among attributes of the numeric type.
Quartile1SkewnessOfNumericAtts
7.6
First quartile of skewness among attributes of the numeric type.
AutoCorrelation
0
Average class difference between consecutive instances.
MeanMutualInformation
Average mutual information between the nominal attributes and the target attribute.
Quartile1StdDevOfNumericAtts
0
First quartile of standard deviation of attributes of the numeric type.
Show all 62 properties

10 tasks

Supervised Classification on cnae-9
0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: Class
Supervised Classification on cnae-9
0 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: Class
Clustering on cnae-9
0 runs - estimation_procedure: 50 times Clustering
Clustering on cnae-9
0 runs - estimation_procedure: 50 times Clustering
Clustering on cnae-9
0 runs - estimation_procedure: 50 times Clustering
Clustering on cnae-9
0 runs - estimation_procedure: 50 times Clustering
Clustering on cnae-9
0 runs - estimation_procedure: 50 times Clustering
Clustering on cnae-9
0 runs - estimation_procedure: 50 times Clustering
Clustering on cnae-9
0 runs - estimation_procedure: 50 times Clustering
Clustering on cnae-9
0 runs - estimation_procedure: 50 times Clustering
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