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
0 missing
V196numeric1 unique values
0 missing
V452numeric1 unique values
0 missing
V708numeric2 unique values
0 missing
V197numeric2 unique values
0 missing
V453numeric1 unique values
0 missing
V709numeric2 unique values
0 missing
V198numeric1 unique values
0 missing
V454numeric1 unique values
0 missing
V710numeric1 unique values
0 missing
V199numeric2 unique values
0 missing
V455numeric1 unique values
0 missing
V711numeric1 unique values
0 missing
V200numeric2 unique values
0 missing
V456numeric1 unique values
0 missing
V712numeric2 unique values
0 missing
V201numeric2 unique values
0 missing
V457numeric1 unique values
0 missing
V713numeric1 unique values
0 missing
V202numeric2 unique values
0 missing
V458numeric1 unique values
0 missing
V714numeric2 unique values
0 missing
V203numeric1 unique values
0 missing
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
0 missing
V717numeric1 unique values
0 missing
V206numeric2 unique values
0 missing
V462numeric1 unique values
0 missing
V718numeric1 unique values
0 missing
V207numeric2 unique values
0 missing
V463numeric1 unique values
0 missing
V719numeric1 unique values
0 missing
V208numeric2 unique values
0 missing
V464numeric1 unique values
0 missing
V720numeric1 unique values
0 missing
V209numeric2 unique values
0 missing
V465numeric2 unique values
0 missing
V721numeric2 unique values
0 missing
V210numeric1 unique values
0 missing
V466numeric1 unique values
0 missing
V722numeric1 unique values
0 missing
V211numeric1 unique values
0 missing
V467numeric2 unique values
0 missing
V723numeric2 unique values
0 missing
V212numeric1 unique values
0 missing
V468numeric1 unique values
0 missing
V724numeric2 unique values
0 missing
V213numeric2 unique values
0 missing
V469numeric1 unique values
0 missing
V725numeric2 unique values
0 missing
V214numeric2 unique values
0 missing
V470numeric2 unique values
0 missing
V726numeric3 unique values
0 missing
V215numeric1 unique values
0 missing
V471numeric1 unique values
0 missing
V727numeric1 unique values
0 missing
V216numeric1 unique values
0 missing
V472numeric2 unique values
0 missing
V728numeric1 unique values
0 missing
V217numeric1 unique values
0 missing
V473numeric1 unique values
0 missing
V729numeric1 unique values
0 missing
V218numeric1 unique values
0 missing
V474numeric2 unique values
0 missing
V730numeric1 unique values
0 missing
V219numeric2 unique values
0 missing
V475numeric1 unique values
0 missing
V731numeric3 unique values
0 missing
V220numeric1 unique values
0 missing
V476numeric2 unique values
0 missing
V732numeric2 unique values
0 missing
V221numeric1 unique values
0 missing
V477numeric2 unique values
0 missing
V733numeric1 unique values
0 missing
V222numeric2 unique values
0 missing
V478numeric1 unique values
0 missing
V734numeric1 unique values
0 missing
V223numeric1 unique values
0 missing
V479numeric1 unique values
0 missing
V735numeric1 unique values
0 missing
V224numeric1 unique values
0 missing
V480numeric1 unique values
0 missing
V736numeric1 unique values
0 missing
V225numeric1 unique values
0 missing
V481numeric1 unique values
0 missing
V737numeric1 unique values
0 missing
V226numeric2 unique values
0 missing
V482numeric2 unique values
0 missing
V738numeric1 unique values
0 missing
V227numeric2 unique values
0 missing
V483numeric1 unique values
0 missing
V739numeric2 unique values
0 missing
V228numeric1 unique values
0 missing
V484numeric1 unique values
0 missing
V740numeric2 unique values
0 missing
V229numeric1 unique values
0 missing
V485numeric1 unique values
0 missing
V741numeric2 unique values
0 missing
V230numeric3 unique values
0 missing
V486numeric1 unique values
0 missing
V742numeric1 unique values
0 missing
V231numeric2 unique values
0 missing
V487numeric1 unique values
0 missing
V743numeric1 unique values
0 missing
V232numeric1 unique values
0 missing
V488numeric1 unique values
0 missing
V744numeric1 unique values
0 missing
V233numeric1 unique values
0 missing
V489numeric2 unique values
0 missing
V745numeric1 unique values
0 missing
V234numeric1 unique values
0 missing
V490numeric2 unique values
0 missing
V746numeric1 unique values
0 missing
V235numeric2 unique values
0 missing
V491numeric1 unique values
0 missing
V747numeric1 unique values
0 missing
V236numeric2 unique values
0 missing
V492numeric2 unique values
0 missing
V748numeric1 unique values
0 missing
V237numeric1 unique values
0 missing
V493numeric2 unique values
0 missing
V749numeric2 unique values
0 missing
V238numeric1 unique values
0 missing
V494numeric2 unique values
0 missing
V750numeric2 unique values
0 missing
V239numeric1 unique values
0 missing
V495numeric2 unique values
0 missing
V751numeric1 unique values
0 missing
V240numeric1 unique values
0 missing
V496numeric1 unique values
0 missing
V752numeric2 unique values
0 missing
V241numeric1 unique values
0 missing
V497numeric1 unique values
0 missing
V753numeric2 unique values
0 missing
V242numeric2 unique values
0 missing
V498numeric1 unique values
0 missing
V754numeric2 unique values
0 missing
V243numeric1 unique values
0 missing
V499numeric2 unique values
0 missing
V755numeric2 unique values
0 missing
V244numeric2 unique values
0 missing
V500numeric2 unique values
0 missing
V756numeric1 unique values
0 missing
V245numeric1 unique values
0 missing
V501numeric1 unique values
0 missing
V757numeric1 unique values
0 missing
V246numeric1 unique values
0 missing
V502numeric1 unique values
0 missing
V758numeric2 unique values
0 missing
V247numeric1 unique values
0 missing
V503numeric1 unique values
0 missing
V759numeric2 unique values
0 missing
V248numeric1 unique values
0 missing
V504numeric1 unique values
0 missing
V760numeric1 unique values
0 missing
V249numeric1 unique values
0 missing
V505numeric1 unique values
0 missing
V761numeric2 unique values
0 missing
V250numeric1 unique values
0 missing
V506numeric1 unique values
0 missing
V762numeric2 unique values
0 missing
V251numeric1 unique values
0 missing
V507numeric1 unique values
0 missing
V763numeric2 unique values
0 missing
V252numeric1 unique values
0 missing
V508numeric1 unique values
0 missing
V764numeric2 unique values
0 missing
V253numeric1 unique values
0 missing
V509numeric1 unique values
0 missing
V765numeric1 unique values
0 missing
V254numeric1 unique values
0 missing
V510numeric2 unique values
0 missing
V766numeric1 unique values
0 missing
V255numeric1 unique values
0 missing
V511numeric2 unique values
0 missing
V767numeric2 unique values
0 missing
V256numeric2 unique values
0 missing
V512numeric1 unique values
0 missing
V768numeric2 unique values
0 missing

62 properties

240
Number of instances (rows) of the dataset.
857
Number of attributes (columns) of the dataset.
2
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
856
Number of numeric attributes.
1
Number of nominal attributes.
Minimal entropy among attributes.
15.49
Second quartile (Median) of skewness among attributes of the numeric type.
120
Number of instances belonging to the most frequent class.
-1.56
Minimum kurtosis among attributes of the numeric type.
0.12
Percentage of binary attributes.
0
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
240
Maximum kurtosis among attributes of the numeric type.
0
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
0.37
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of missing values.
240
Third quartile of kurtosis among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
2
The minimal number of distinct values among attributes of the nominal type.
99.88
Percentage of numeric attributes.
0
Third quartile of means among attributes of the numeric type.
2
The maximum number of distinct values among attributes of the nominal type.
0.67
Minimum skewness among attributes of the numeric type.
0.12
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
15.49
Maximum skewness among attributes of the numeric type.
0
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
15.49
Third quartile of skewness among attributes of the numeric type.
0.55
Maximum standard deviation of attributes of the numeric type.
50
Percentage of instances belonging to the least frequent class.
56.21
First quartile of kurtosis among attributes of the numeric type.
0.06
Third quartile of standard deviation of attributes of the numeric type.
Average entropy of the attributes.
120
Number of instances belonging to the least frequent class.
0
First quartile of means among attributes of the numeric type.
0
Standard deviation of the number of distinct values among attributes of the nominal type.
152.24
Mean kurtosis among attributes of the numeric type.
1
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
0.01
Mean of means among attributes of the numeric type.
7.6
First quartile of skewness among attributes of the numeric type.
Average mutual information between the nominal attributes and the target attribute.
0
First quartile of standard deviation of attributes of the numeric type.
0
Average class difference between consecutive instances.
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
Second quartile (Median) of entropy among attributes.
1
Entropy of the target attribute values.
2
Average number of distinct values among the attributes of the nominal type.
240
Second quartile (Median) of kurtosis among attributes of the numeric type.
3.57
Number of attributes divided by the number of instances.
11.46
Mean skewness among attributes of the numeric type.
0
Second quartile (Median) of means among attributes of the numeric type.
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
0.04
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
50
Percentage of instances belonging to the most frequent class.

1 tasks

0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: Class
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