Data
cnae-9

cnae-9

active ARFF Publicly available Visibility: public Uploaded 21-05-2015 by Rafael Gomes Mantovani
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  • Chemistry Life Science OpenML-CC18 OpenML100 study_123 study_135 study_14 study_218 study_52 study_7 study_98 study_99 study_225 study_271 study_240 study_253 study_285 study_379 study_446 study_447 study_448 study_449 study_275
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Author: Patrick Marques Ciarelli, Elias Oliviera Source: [UCI](https://archive.ics.uci.edu/ml/datasets/CNAE-9) - 2010 Please cite: ### Description This is a data set containing 1080 documents of free text business descriptions of Brazilian companies categorized into a subset of 9 categories. ### Source ``` Patrick Marques Ciarelli, pciarelli '@' lcad.inf.ufes.br, Department of Electrical Engineering, Federal University of Espirito Santo Elias Oliveira, elias '@' lcad.inf.ufes.br, Department of Information Science, Federal University of Espirito Santo ``` ### Data Set Information This is a data set containing 1080 documents of free text business descriptions of Brazilian companies categorized into a subset of 9 categories cataloged in a table called National Classification of Economic Activities (Classificação Nacional de Atividade Econômicas - CNAE). The original texts were preprocessed to obtain the current data set: initially, it was kept only letters and then it was removed prepositions of the texts. Next, the words were transformed to their canonical form. Finally, each document was represented as a vector, where the weight of each word is its frequency in the document. This data set is highly sparse (99.22% of the matrix is filled with zeros). ### Attribute Information In the dataset there are 857 attributes, 1 attributes with the class of instance and 856 with word frequency: ``` 1. category: range 1 - 9 (integer) 2. 857. word frequency: (integer) ``` ### Relevant Papers Patrick Marques Ciarelli, Elias Oliveira, 'Agglomeration and Elimination of Terms for Dimensionality Reduction', Ninth International Conference on Intelligent Systems Design and Applications, pp.547-552, 2009 Patrick Marques Ciarelli, Elias Oliveira, Evandro O. T. Salles, 'An Evolving System Based on Probabilistic Neural Network', Brazilian Symposium on Artificial Neural Network, 2010

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V692numeric2 unique values
0 missing
V181numeric2 unique values
0 missing
V437numeric2 unique values
0 missing
V693numeric2 unique values
0 missing
V182numeric2 unique values
0 missing
V438numeric2 unique values
0 missing
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0 missing
V183numeric2 unique values
0 missing
V439numeric2 unique values
0 missing
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0 missing
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0 missing
V440numeric2 unique values
0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
V443numeric2 unique values
0 missing
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0 missing
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0 missing
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0 missing
V700numeric2 unique values
0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
V455numeric2 unique values
0 missing
V711numeric2 unique values
0 missing
V200numeric2 unique values
0 missing
V456numeric2 unique values
0 missing
V712numeric2 unique values
0 missing
V201numeric2 unique values
0 missing
V457numeric2 unique values
0 missing
V713numeric2 unique values
0 missing
V202numeric3 unique values
0 missing
V458numeric2 unique values
0 missing
V714numeric2 unique values
0 missing
V203numeric2 unique values
0 missing
V459numeric2 unique values
0 missing
V715numeric3 unique values
0 missing
V204numeric2 unique values
0 missing
V460numeric2 unique values
0 missing
V716numeric2 unique values
0 missing
V205numeric2 unique values
0 missing
V461numeric2 unique values
0 missing
V717numeric2 unique values
0 missing
V206numeric2 unique values
0 missing
V462numeric2 unique values
0 missing
V718numeric2 unique values
0 missing
V207numeric2 unique values
0 missing
V463numeric2 unique values
0 missing
V719numeric2 unique values
0 missing
V208numeric2 unique values
0 missing
V464numeric2 unique values
0 missing
V720numeric2 unique values
0 missing
V209numeric2 unique values
0 missing
V465numeric2 unique values
0 missing
V721numeric2 unique values
0 missing
V210numeric2 unique values
0 missing
V466numeric2 unique values
0 missing
V722numeric2 unique values
0 missing
V211numeric2 unique values
0 missing
V467numeric2 unique values
0 missing
V723numeric2 unique values
0 missing
V212numeric2 unique values
0 missing
V468numeric2 unique values
0 missing
V724numeric3 unique values
0 missing
V213numeric2 unique values
0 missing
V469numeric3 unique values
0 missing
V725numeric2 unique values
0 missing
V214numeric2 unique values
0 missing
V470numeric2 unique values
0 missing
V726numeric3 unique values
0 missing
V215numeric2 unique values
0 missing
V471numeric2 unique values
0 missing
V727numeric2 unique values
0 missing
V216numeric2 unique values
0 missing
V472numeric2 unique values
0 missing
V728numeric2 unique values
0 missing
V217numeric2 unique values
0 missing
V473numeric2 unique values
0 missing
V729numeric2 unique values
0 missing
V218numeric2 unique values
0 missing
V474numeric3 unique values
0 missing
V730numeric2 unique values
0 missing
V219numeric2 unique values
0 missing
V475numeric2 unique values
0 missing
V731numeric3 unique values
0 missing
V220numeric2 unique values
0 missing
V476numeric2 unique values
0 missing
V732numeric2 unique values
0 missing
V221numeric2 unique values
0 missing
V477numeric2 unique values
0 missing
V733numeric2 unique values
0 missing
V222numeric2 unique values
0 missing
V478numeric2 unique values
0 missing
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0 missing
V223numeric2 unique values
0 missing
V479numeric2 unique values
0 missing
V735numeric2 unique values
0 missing
V224numeric2 unique values
0 missing
V480numeric2 unique values
0 missing
V736numeric2 unique values
0 missing
V225numeric2 unique values
0 missing
V481numeric2 unique values
0 missing
V737numeric2 unique values
0 missing
V226numeric2 unique values
0 missing
V482numeric2 unique values
0 missing
V738numeric2 unique values
0 missing
V227numeric2 unique values
0 missing
V483numeric2 unique values
0 missing
V739numeric2 unique values
0 missing
V228numeric2 unique values
0 missing
V484numeric2 unique values
0 missing
V740numeric2 unique values
0 missing
V229numeric2 unique values
0 missing
V485numeric2 unique values
0 missing
V741numeric2 unique values
0 missing
V230numeric3 unique values
0 missing
V486numeric2 unique values
0 missing
V742numeric2 unique values
0 missing
V231numeric2 unique values
0 missing
V487numeric3 unique values
0 missing
V743numeric2 unique values
0 missing
V232numeric3 unique values
0 missing
V488numeric2 unique values
0 missing
V744numeric2 unique values
0 missing
V233numeric2 unique values
0 missing
V489numeric2 unique values
0 missing
V745numeric2 unique values
0 missing
V234numeric2 unique values
0 missing
V490numeric2 unique values
0 missing
V746numeric2 unique values
0 missing
V235numeric2 unique values
0 missing
V491numeric2 unique values
0 missing
V747numeric2 unique values
0 missing
V236numeric2 unique values
0 missing
V492numeric2 unique values
0 missing
V748numeric2 unique values
0 missing
V237numeric2 unique values
0 missing
V493numeric2 unique values
0 missing
V749numeric2 unique values
0 missing
V238numeric2 unique values
0 missing
V494numeric2 unique values
0 missing
V750numeric2 unique values
0 missing
V239numeric2 unique values
0 missing
V495numeric2 unique values
0 missing
V751numeric3 unique values
0 missing
V240numeric2 unique values
0 missing
V496numeric2 unique values
0 missing
V752numeric2 unique values
0 missing
V241numeric2 unique values
0 missing
V497numeric2 unique values
0 missing
V753numeric2 unique values
0 missing
V242numeric2 unique values
0 missing
V498numeric2 unique values
0 missing
V754numeric2 unique values
0 missing
V243numeric2 unique values
0 missing
V499numeric3 unique values
0 missing
V755numeric2 unique values
0 missing
V244numeric2 unique values
0 missing
V500numeric2 unique values
0 missing
V756numeric2 unique values
0 missing
V245numeric2 unique values
0 missing
V501numeric2 unique values
0 missing
V757numeric2 unique values
0 missing
V246numeric2 unique values
0 missing
V502numeric2 unique values
0 missing
V758numeric2 unique values
0 missing
V247numeric2 unique values
0 missing
V503numeric2 unique values
0 missing
V759numeric2 unique values
0 missing
V248numeric2 unique values
0 missing
V504numeric2 unique values
0 missing
V760numeric2 unique values
0 missing
V249numeric2 unique values
0 missing
V505numeric2 unique values
0 missing
V761numeric2 unique values
0 missing
V250numeric2 unique values
0 missing
V506numeric2 unique values
0 missing
V762numeric2 unique values
0 missing
V251numeric2 unique values
0 missing
V507numeric2 unique values
0 missing
V763numeric2 unique values
0 missing
V252numeric2 unique values
0 missing
V508numeric2 unique values
0 missing
V764numeric2 unique values
0 missing
V253numeric2 unique values
0 missing
V509numeric2 unique values
0 missing
V765numeric2 unique values
0 missing
V254numeric2 unique values
0 missing
V510numeric2 unique values
0 missing
V766numeric2 unique values
0 missing
V255numeric2 unique values
0 missing
V511numeric2 unique values
0 missing
V767numeric2 unique values
0 missing
V256numeric2 unique values
0 missing
V512numeric2 unique values
0 missing
V768numeric2 unique values
0 missing

107 properties

1080
Number of instances (rows) of the dataset.
857
Number of attributes (columns) of the dataset.
9
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.
11.11
Percentage of instances belonging to the most frequent class.
0.07
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
0.23
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.78
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.19
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
120
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
537.49
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.74
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
3.17
Entropy of the target attribute values.
0.79
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
Maximum entropy among attributes.
-1.26
Minimum kurtosis among attributes of the numeric type.
0
Second quartile (Median) of means among attributes of the numeric type.
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.65
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
1080
Maximum kurtosis among attributes of the numeric type.
0
Minimum of means among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.23
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.81
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
0.44
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
23.21
Second quartile (Median) of skewness among attributes of the numeric type.
0.74
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.09
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum mutual information between the nominal attributes and the target attribute.
9
The minimal number of distinct values among attributes of the nominal type.
0
Percentage of binary attributes.
0.04
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.88
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.79
Number of attributes divided by the number of instances.
9
The maximum number of distinct values among attributes of the nominal type.
0.63
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
0.22
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
32.86
Maximum skewness among attributes of the numeric type.
0.03
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
1080
Third quartile of kurtosis among attributes of the numeric type.
0
Average class difference between consecutive instances.
0.75
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.96
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
0.62
Maximum standard deviation of attributes of the numeric type.
11.11
Percentage of instances belonging to the least frequent class.
99.88
Percentage of numeric attributes.
0
Third quartile of means among attributes of the numeric type.
0.96
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.88
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.14
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Average entropy of the attributes.
120
Number of instances belonging to the least frequent class.
0.12
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
0.19
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.22
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.85
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
636.46
Mean kurtosis among attributes of the numeric type.
0.99
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of entropy among attributes.
32.86
Third quartile of skewness among attributes of the numeric type.
0.78
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.75
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.96
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0.01
Mean of means among attributes of the numeric type.
0.08
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
211.99
First quartile of kurtosis among attributes of the numeric type.
0.07
Third quartile of standard deviation of attributes of the numeric type.
0.96
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.88
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.14
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Average mutual information between the nominal attributes and the target attribute.
0.91
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0
First quartile of means among attributes of the numeric type.
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.19
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.22
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.85
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
0
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
0.23
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.78
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.75
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.96
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
9
Average number of distinct values among the attributes of the nominal type.
14.61
First quartile of skewness among attributes of the numeric type.
0.74
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.96
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0
Standard deviation of the number of distinct values among attributes of the nominal type.
0.14
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
0.85
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
23.16
Mean skewness among attributes of the numeric type.
0.03
First quartile of standard deviation of attributes of the numeric type.
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.19
Error rate achieved by the landmarker weka.classifiers.lazy.IBk -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.91
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk

59 tasks

22833 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: Class
31 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: Class
5 runs - estimation_procedure: 33% Holdout set - target_feature: Class
1 runs - estimation_procedure: 5 times 2-fold Crossvalidation - target_feature: Class
0 runs - estimation_procedure: 20% Holdout (Ordered) - target_feature: Class
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - target_feature: Class
0 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: Class
0 runs - estimation_procedure: 4-fold Crossvalidation - target_feature: Class
0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: Class
0 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: classification problem
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature:
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - target_feature: Class
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
1303 runs - target_feature: Class
1303 runs - target_feature: Class
1302 runs - target_feature: Class
1301 runs - target_feature: Class
1301 runs - target_feature: Class
1300 runs - target_feature: Class
1300 runs - target_feature: Class
1300 runs - target_feature: Class
1299 runs - target_feature: Class
0 runs - target_feature: Class
0 runs - target_feature: Class
0 runs - target_feature: Class
0 runs - target_feature: Class
0 runs - target_feature: Class
0 runs - target_feature: Class
0 runs - target_feature: Class
0 runs - target_feature: Class
0 runs - target_feature: Class
0 runs - target_feature: Class
0 runs - target_feature: Class
0 runs - target_feature: Class
0 runs - target_feature: Class
0 runs - target_feature: Class
0 runs - target_feature: Class
0 runs - target_feature: Class
0 runs - target_feature: Class
0 runs - target_feature: Class
0 runs - target_feature: Class
0 runs - target_feature: Class
0 runs - target_feature: Class
0 runs - target_feature: Class
0 runs - target_feature: Class
0 runs - target_feature: Class
0 runs - target_feature: Class
0 runs - target_feature: Class
0 runs - target_feature: Class
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