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adult-census

adult-census

active ARFF Publicly available Visibility: public Uploaded 07-10-2014 by Felicia West
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Author: Ronny Kohavi and Barry Becker Source: [MLRR](http://axon.cs.byu.edu:5000/) Please cite: Ron Kohavi, "Scaling Up the Accuracy of Naive-Bayes Classifiers: a Decision-Tree Hybrid", Proceedings of the Second International Conference on Knowledge Discovery and Data Mining, 1996 Dataset from the MLRR repository: http://axon.cs.byu.edu:5000/ Note: this dataset is identical to the version stored in UCI, but only includes the training data, not the test data. See [adult (2)](http://openml.org/d/1590) for the complete data.

16 features

class (target)nominal2 unique values
0 missing
ID (row identifier)numeric32561 unique values
0 missing
agenumeric73 unique values
0 missing
workclassnominal8 unique values
1836 missing
fnlwgt:numeric21648 unique values
0 missing
education:nominal16 unique values
0 missing
education-num:numeric16 unique values
0 missing
marital-status:nominal7 unique values
0 missing
occupation:nominal14 unique values
1843 missing
relationship:nominal6 unique values
0 missing
race:nominal5 unique values
0 missing
sex:nominal2 unique values
0 missing
capital-gain:numeric119 unique values
0 missing
capital-loss:numeric92 unique values
0 missing
hours-per-week:numeric94 unique values
0 missing
native-country:nominal41 unique values
583 missing
Show all 16 features

107 properties

NumberOfInstances
32561
Number of instances (rows) of the dataset.
NumberOfFeatures
16
Number of attributes (columns) of the dataset.
NumberOfClasses
2
Number of distinct values of the target attribute (if it is nominal).
NumberOfMissingValues
4262
Number of missing values in the dataset.
NumberOfInstancesWithMissingValues
2399
Number of instances with at least one value missing.
NumberOfNumericFeatures
7
Number of numeric attributes.
NumberOfSymbolicFeatures
9
Number of nominal attributes.
AutoCorrelation
0.63
Average class difference between consecutive instances.
CfsSubsetEval_DecisionStumpAUC
0.86
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
CfsSubsetEval_DecisionStumpErrRate
0.15
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
CfsSubsetEval_DecisionStumpKappa
0.55
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
CfsSubsetEval_NaiveBayesAUC
0.86
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
CfsSubsetEval_NaiveBayesErrRate
0.15
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
CfsSubsetEval_NaiveBayesKappa
0.55
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
CfsSubsetEval_kNN1NAUC
0.86
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
CfsSubsetEval_kNN1NErrRate
0.15
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
CfsSubsetEval_kNN1NKappa
0.55
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
ClassEntropy
0.8
Entropy of the target attribute values.
DecisionStumpAUC
0.76
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpErrRate
0.24
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpKappa
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
Dimensionality
0
Number of attributes divided by the number of instances.
EquivalentNumberOfAtts
11.04
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
J48.00001.AUC
0.88
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.ErrRate
0.14
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.Kappa
0.58
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.0001.AUC
0.88
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.ErrRate
0.14
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.Kappa
0.58
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.001.AUC
0.88
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.ErrRate
0.14
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.Kappa
0.58
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
MajorityClassPercentage
75.92
Percentage of instances belonging to the most frequent class.
MajorityClassSize
24720
Number of instances belonging to the most frequent class.
MaxAttributeEntropy
3.44
Maximum entropy among attributes.
MaxKurtosisOfNumericAtts
154.8
Maximum kurtosis among attributes of the numeric type.
MaxMeansOfNumericAtts
189778.37
Maximum of means among attributes of the numeric type.
MaxMutualInformation
0.17
Maximum mutual information between the nominal attributes and the target attribute.
MaxNominalAttDistinctValues
41
The maximum number of distinct values among attributes of the nominal type.
MaxSkewnessOfNumericAtts
11.95
Maximum skewness among attributes of the numeric type.
MaxStdDevOfNumericAtts
105549.98
Maximum standard deviation of attributes of the numeric type.
MeanAttributeEntropy
1.78
Average entropy of the attributes.
MeanKurtosisOfNumericAtts
30.79
Mean kurtosis among attributes of the numeric type.
MeanMeansOfNumericAtts
31838.74
Mean of means among attributes of the numeric type.
MeanMutualInformation
0.07
Average mutual information between the nominal attributes and the target attribute.
MeanNoiseToSignalRatio
23.69
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
MeanNominalAttDistinctValues
11.22
Average number of distinct values among the attributes of the nominal type.
MeanSkewnessOfNumericAtts
3.08
Mean skewness among attributes of the numeric type.
MeanStdDevOfNumericAtts
18894.47
Mean standard deviation of attributes of the numeric type.
MinAttributeEntropy
0.8
Minimal entropy among attributes.
MinKurtosisOfNumericAtts
-0.17
Minimum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
10.08
Minimum of means among attributes of the numeric type.
MinMutualInformation
0.01
Minimal mutual information between the nominal attributes and the target attribute.
MinNominalAttDistinctValues
2
The minimal number of distinct values among attributes of the nominal type.
MinSkewnessOfNumericAtts
-0.31
Minimum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
2.57
Minimum standard deviation of attributes of the numeric type.
MinorityClassPercentage
24.08
Percentage of instances belonging to the least frequent class.
MinorityClassSize
7841
Number of instances belonging to the least frequent class.
NaiveBayesAUC
0.89
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesErrRate
0.17
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesKappa
0.49
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NumberOfBinaryFeatures
2
Number of binary attributes.
PercentageOfBinaryFeatures
12.5
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
7.37
Percentage of instances having missing values.
PercentageOfMissingValues
0.82
Percentage of missing values.
PercentageOfNumericFeatures
43.75
Percentage of numeric attributes.
PercentageOfSymbolicFeatures
56.25
Percentage of nominal attributes.
Quartile1AttributeEntropy
0.84
First quartile of entropy among attributes.
Quartile1KurtosisOfNumericAtts
0.43
First quartile of kurtosis among attributes of the numeric type.
Quartile1MeansOfNumericAtts
31.46
First quartile of means among attributes of the numeric type.
Quartile1MutualInformation
0.01
First quartile of mutual information between the nominal attributes and the target attribute.
Quartile1SkewnessOfNumericAtts
0.09
First quartile of skewness among attributes of the numeric type.
Quartile1StdDevOfNumericAtts
9.9
First quartile of standard deviation of attributes of the numeric type.
Quartile2AttributeEntropy
1.6
Second quartile (Median) of entropy among attributes.
Quartile2KurtosisOfNumericAtts
4.57
Second quartile (Median) of kurtosis among attributes of the numeric type.
Quartile2MeansOfNumericAtts
63.87
Second quartile (Median) of means among attributes of the numeric type.
Quartile2MutualInformation
0.06
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Quartile2SkewnessOfNumericAtts
1
Second quartile (Median) of skewness among attributes of the numeric type.
Quartile2StdDevOfNumericAtts
208.3
Second quartile (Median) of standard deviation of attributes of the numeric type.
Quartile3AttributeEntropy
2.74
Third quartile of entropy among attributes.
Quartile3KurtosisOfNumericAtts
53.98
Third quartile of kurtosis among attributes of the numeric type.
Quartile3MeansOfNumericAtts
48252.83
Third quartile of means among attributes of the numeric type.
Quartile3MutualInformation
0.14
Third quartile of mutual information between the nominal attributes and the target attribute.
Quartile3SkewnessOfNumericAtts
6.43
Third quartile of skewness among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
31926.46
Third quartile of standard deviation of attributes of the numeric type.
REPTreeDepth1AUC
0.87
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1ErrRate
0.16
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1Kappa
0.54
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth2AUC
0.87
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2ErrRate
0.16
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2Kappa
0.54
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth3AUC
0.87
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3ErrRate
0.16
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3Kappa
0.54
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
RandomTreeDepth1AUC
0.75
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1ErrRate
0.19
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1Kappa
0.47
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth2AUC
0.75
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2ErrRate
0.19
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2Kappa
0.47
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth3AUC
0.75
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3ErrRate
0.19
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3Kappa
0.47
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
StdvNominalAttDistinctValues
12.15
Standard deviation of the number of distinct values among attributes of the nominal type.
kNN1NAUC
0.71
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NErrRate
0.21
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NKappa
0.42
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
Show all 107 properties

26 tasks

Supervised Classification on adult-census
68 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
Supervised Classification on adult-census
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
Supervised Classification on adult-census
0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: precision - target_feature: class
Supervised Classification on adult-census
0 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: class
Supervised Classification on adult-census
0 runs - estimation_procedure: 4-fold Crossvalidation - target_feature: class
Learning Curve on adult-census
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on adult-census
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on adult-census
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on adult-census
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on adult-census
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on adult-census
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on adult-census
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on adult-census
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on adult-census
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Supervised Data Stream Classification on adult-census
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: class
Clustering on adult-census
0 runs
Clustering on adult-census
0 runs - estimation_procedure: 50 times Clustering
Clustering on adult-census
0 runs - estimation_procedure: 50 times Clustering
Clustering on adult-census
0 runs - estimation_procedure: 50 times Clustering
Clustering on adult-census
0 runs - estimation_procedure: 50 times Clustering
Clustering on adult-census
0 runs - estimation_procedure: 50 times Clustering
Clustering on adult-census
0 runs - estimation_procedure: 50 times Clustering
Clustering on adult-census
0 runs - estimation_procedure: 50 times Clustering
Clustering on adult-census
0 runs - estimation_procedure: 50 times Clustering
Clustering on adult-census
0 runs - estimation_procedure: 50 times Clustering
Clustering on adult-census
0 runs - estimation_procedure: 50 times Clustering
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