Data
adult-census

adult-census

active ARFF Publicly available Visibility: public Uploaded 07-10-2014 by Joaquin Vanschoren
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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

107 properties

32561
Number of instances (rows) of the dataset.
16
Number of attributes (columns) of the dataset.
2
Number of distinct values of the target attribute (if it is nominal).
4262
Number of missing values in the dataset.
2399
Number of instances with at least one value missing.
7
Number of numeric attributes.
9
Number of nominal attributes.
0.54
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
189778.37
Maximum of means among attributes of the numeric type.
0.01
Minimal mutual information between the nominal attributes and the target attribute.
1
Second quartile (Median) of skewness among attributes of the numeric type.
0.75
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0
Number of attributes divided by the number of instances.
0.17
Maximum mutual information between the nominal attributes and the target attribute.
2
The minimal number of distinct values among attributes of the nominal type.
12.5
Percentage of binary attributes.
208.3
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.19
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
11.04
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
41
The maximum number of distinct values among attributes of the nominal type.
-0.31
Minimum skewness among attributes of the numeric type.
7.37
Percentage of instances having missing values.
2.74
Third quartile of entropy among attributes.
0.47
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.88
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
11.95
Maximum skewness among attributes of the numeric type.
2.57
Minimum standard deviation of attributes of the numeric type.
0.82
Percentage of missing values.
53.98
Third quartile of kurtosis among attributes of the numeric type.
0.63
Average class difference between consecutive instances.
0.75
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
105549.98
Maximum standard deviation of attributes of the numeric type.
24.08
Percentage of instances belonging to the least frequent class.
43.75
Percentage of numeric attributes.
48252.83
Third quartile of means among attributes of the numeric type.
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
0.19
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.58
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
1.78
Average entropy of the attributes.
7841
Number of instances belonging to the least frequent class.
56.25
Percentage of nominal attributes.
0.14
Third quartile of mutual information between the nominal attributes and the target attribute.
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
0.47
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.88
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
30.79
Mean kurtosis among attributes of the numeric type.
0.89
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.84
First quartile of entropy among attributes.
6.43
Third quartile of skewness among attributes of the numeric type.
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
0.75
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
31838.74
Mean of means among attributes of the numeric type.
0.17
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.43
First quartile of kurtosis among attributes of the numeric type.
31926.46
Third quartile of standard deviation of attributes of the numeric type.
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
0.19
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.58
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0.07
Average mutual information between the nominal attributes and the target attribute.
0.49
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
31.46
First quartile of means among attributes of the numeric type.
0.87
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
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
0.47
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.88
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
23.69
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
2
Number of binary attributes.
0.01
First quartile of mutual information between the nominal attributes and the target attribute.
0.16
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
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
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
12.15
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
11.22
Average number of distinct values among the attributes of the nominal type.
0.09
First quartile of skewness among attributes of the numeric type.
0.54
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
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
0.71
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.58
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
3.08
Mean skewness among attributes of the numeric type.
9.9
First quartile of standard deviation of attributes of the numeric type.
0.87
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
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
0.21
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
75.92
Percentage of instances belonging to the most frequent class.
18894.47
Mean standard deviation of attributes of the numeric type.
1.6
Second quartile (Median) of entropy among attributes.
0.16
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.8
Entropy of the target attribute values.
0.42
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
24720
Number of instances belonging to the most frequent class.
0.8
Minimal entropy among attributes.
4.57
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.54
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.87
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.76
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
3.44
Maximum entropy among attributes.
-0.17
Minimum kurtosis among attributes of the numeric type.
63.87
Second quartile (Median) of means among attributes of the numeric type.
0.16
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.24
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
154.8
Maximum kurtosis among attributes of the numeric type.
10.08
Minimum of means among attributes of the numeric type.
0.06
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.

26 tasks

68 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
0 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: class
0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: precision - target_feature: class
0 runs - estimation_procedure: 4-fold Crossvalidation - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: Interleaved Test then Train - 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
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
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