Data
BNG(anneal,1000,1)

BNG(anneal,1000,1)

active ARFF public domain Visibility: public Uploaded 22-02-2015 by Jan van Rijn
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39 features

class (target)nominal6 unique values
0 missing
familynominal10 unique values
0 missing
product-typenominal3 unique values
0 missing
steelnominal9 unique values
0 missing
carbonnumeric304377 unique values
0 missing
hardnessnumeric247949 unique values
0 missing
temper_rollingnominal2 unique values
0 missing
conditionnominal4 unique values
0 missing
formabilitynominal6 unique values
0 missing
strengthnumeric274446 unique values
0 missing
non-ageingnominal2 unique values
0 missing
surface-finishnominal3 unique values
0 missing
surface-qualitynominal5 unique values
0 missing
enamelabilitynominal6 unique values
0 missing
bcnominal2 unique values
0 missing
bfnominal2 unique values
0 missing
btnominal2 unique values
0 missing
bw%2Fmenominal3 unique values
0 missing
blnominal2 unique values
0 missing
mnominal2 unique values
0 missing
chromnominal2 unique values
0 missing
phosnominal2 unique values
0 missing
cbondnominal2 unique values
0 missing
marvinominal2 unique values
0 missing
exptlnominal2 unique values
0 missing
ferronominal2 unique values
0 missing
corrnominal2 unique values
0 missing
blue%2Fbright%2Fvarn%2Fcleannominal5 unique values
0 missing
lustrenominal2 unique values
0 missing
jurofmnominal2 unique values
0 missing
snominal2 unique values
0 missing
pnominal2 unique values
0 missing
shapenominal2 unique values
0 missing
thicknumeric738233 unique values
0 missing
widthnumeric595533 unique values
0 missing
lennumeric294108 unique values
0 missing
oilnominal3 unique values
0 missing
borenominal4 unique values
0 missing
packingnominal4 unique values
0 missing

107 properties

1000000
Number of instances (rows) of the dataset.
39
Number of attributes (columns) of the dataset.
6
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.
6
Number of numeric attributes.
33
Number of nominal attributes.
0.96
Second quartile (Median) of skewness among attributes of the numeric type.
0.75
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
1399.8
Maximum of means among attributes of the numeric type.
0
Minimal mutual information between the nominal attributes and the target attribute.
124.59
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.84
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.
0.08
Maximum mutual information between the nominal attributes and the target attribute.
2
The minimal number of distinct values among attributes of the nominal type.
48.72
Percentage of binary attributes.
1.41
Third quartile of entropy among attributes.
0.15
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
48.92
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
10
The maximum number of distinct values among attributes of the nominal type.
0.06
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
-0.05
Third quartile of kurtosis among attributes of the numeric type.
0.6
Average class difference between consecutive instances.
0.62
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.92
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
1.37
Maximum skewness among attributes of the numeric type.
0.91
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
940.11
Third quartile of means among attributes of the numeric type.
0.89
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
0.84
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.09
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
1862.06
Maximum standard deviation of attributes of the numeric type.
0.06
Percentage of instances belonging to the least frequent class.
15.38
Percentage of numeric attributes.
0.03
Third quartile of mutual information between the nominal attributes and the target attribute.
0.13
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
0.15
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.77
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
1.04
Average entropy of the attributes.
555
Number of instances belonging to the least frequent class.
84.62
Percentage of nominal attributes.
1.18
Third quartile of skewness among attributes of the numeric type.
0.63
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
0.62
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.92
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
-0.54
Mean kurtosis among attributes of the numeric type.
0.87
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.5
First quartile of entropy among attributes.
771.76
Third quartile of standard deviation of attributes of the numeric type.
0.89
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
0.84
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.09
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
398.1
Mean of means among attributes of the numeric type.
0.22
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
-1.02
First quartile of kurtosis among attributes of the numeric type.
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.13
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
0.15
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.77
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0.02
Average mutual information between the nominal attributes and the target attribute.
0.48
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
13.23
First quartile of means among attributes of the numeric type.
0.01
First quartile of mutual information between the nominal attributes and the target attribute.
0.1
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.63
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
0.62
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.92
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
41.44
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
19
Number of binary attributes.
0.28
First quartile of skewness among attributes of the numeric type.
0.75
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.89
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
2.08
Standard deviation of the number of distinct values among attributes of the nominal type.
0.09
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
3.3
Average number of distinct values among the attributes of the nominal type.
19.38
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
0.13
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
0.81
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.77
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
0.8
Mean skewness among attributes of the numeric type.
0.92
Second quartile (Median) of entropy among attributes.
0.1
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.63
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
0.13
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
75.97
Percentage of instances belonging to the most frequent class.
424.33
Mean standard deviation of attributes of the numeric type.
-0.77
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.75
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
1.2
Entropy of the target attribute values.
0.64
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
759652
Number of instances belonging to the most frequent class.
0.26
Minimal entropy among attributes.
91.73
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
0.64
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
2.75
Maximum entropy among attributes.
-1.45
Minimum kurtosis among attributes of the numeric type.
0.02
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.1
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.24
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
1.04
Maximum kurtosis among attributes of the numeric type.
1.26
Minimum of means among attributes of the numeric type.

12 tasks

0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: precision - target_feature: class
0 runs - estimation_procedure: 33% Holdout set - 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
9 runs - estimation_procedure: Interleaved Test then Train - target_feature: class
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
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