Data
BNG(cylinder-bands)

BNG(cylinder-bands)

active ARFF Publicly available Visibility: public Uploaded 29-04-2014 by Jan van Rijn
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40 features

band_type (target)nominal2 unique values
0 missing
timestampnominal297 unique values
0 missing
cylinder_numbernominal429 unique values
0 missing
customernominal72 unique values
0 missing
job_numbernumeric999952 unique values
0 missing
grain_screenednominal3 unique values
0 missing
ink_colornominal2 unique values
0 missing
proof_on_ctd_inknominal3 unique values
0 missing
blade_mfgnominal3 unique values
0 missing
cylinder_divisionnominal2 unique values
0 missing
paper_typenominal4 unique values
0 missing
ink_typenominal3 unique values
0 missing
direct_steamnominal3 unique values
0 missing
solvent_typenominal3 unique values
0 missing
type_on_cylindernominal2 unique values
0 missing
press_typenominal4 unique values
0 missing
pressnominal8 unique values
0 missing
unit_numbernumeric201945 unique values
0 missing
cylinder_sizenominal4 unique values
0 missing
paper_mill_locationnominal5 unique values
0 missing
plating_tanknominal3 unique values
0 missing
proof_cutnumeric764997 unique values
0 missing
viscositynumeric980008 unique values
0 missing
calipernominal21 unique values
0 missing
ink_temperaturenumeric844315 unique values
0 missing
humifitynumeric979087 unique values
0 missing
roughnessnumeric324578 unique values
0 missing
blade_pressurenumeric918101 unique values
0 missing
varnish_pctnumeric542830 unique values
0 missing
press_speednumeric999476 unique values
0 missing
ink_pctnumeric937669 unique values
0 missing
solvent_pctnumeric942500 unique values
0 missing
ESA_Voltagenumeric296981 unique values
0 missing
ESA_Amperagenumeric4 unique values
0 missing
waxnumeric374365 unique values
0 missing
hardenernumeric517022 unique values
0 missing
roller_durometernumeric940509 unique values
0 missing
current_densitynominal7 unique values
0 missing
anode_space_rationumeric769165 unique values
0 missing
chrome_contentnominal3 unique values
0 missing

107 properties

1000000
Number of instances (rows) of the dataset.
40
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.
18
Number of numeric attributes.
22
Number of nominal attributes.
0.37
Second quartile (Median) of skewness among attributes of the numeric type.
0.53
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.14
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
37432.04
Maximum of means among attributes of the numeric type.
0
Minimal mutual information between the nominal attributes and the target attribute.
10
Percentage of binary attributes.
4.76
Second quartile (Median) of standard deviation of 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.
0.25
Maximum mutual information between the nominal attributes and the target attribute.
2
The minimal number of distinct values among attributes of the nominal type.
0
Percentage of instances having missing values.
2.45
Third quartile of entropy among attributes.
0.26
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
31.07
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
429
The maximum number of distinct values among attributes of the nominal type.
-1.66
Minimum skewness among attributes of the numeric type.
0
Percentage of missing values.
2.37
Third quartile of kurtosis among attributes of the numeric type.
0.51
Average class difference between consecutive instances.
0.46
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.83
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
9.84
Maximum skewness among attributes of the numeric type.
0.19
Minimum standard deviation of attributes of the numeric type.
45
Percentage of numeric attributes.
61.43
Third quartile of means among attributes of the numeric type.
0.82
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
0.75
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.21
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
8898.91
Maximum standard deviation of attributes of the numeric type.
42.19
Percentage of instances belonging to the least frequent class.
55
Percentage of nominal attributes.
0.03
Third quartile of mutual information between the nominal attributes and the target attribute.
0.21
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
0.26
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
2
Average entropy of the attributes.
421938
Number of instances belonging to the least frequent class.
0.43
First quartile of entropy among attributes.
1.14
Third quartile of skewness among attributes of the numeric type.
0.58
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
0.46
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.83
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
6.42
Mean kurtosis among attributes of the numeric type.
0.91
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
-0.28
First quartile of kurtosis among attributes of the numeric type.
8.27
Third quartile of standard deviation of attributes of the numeric type.
0.82
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
0.75
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.21
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
2207.84
Mean of means among attributes of the numeric type.
0.17
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
2.12
First quartile of means among attributes of the numeric type.
0.81
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.21
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
0.26
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
0.03
Average mutual information between the nominal attributes and the target attribute.
0.66
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0
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
0.58
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
0.46
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.83
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
62.15
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
4
Number of binary attributes.
-0.09
First quartile of skewness among attributes of the numeric type.
0.53
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.82
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
107.51
Standard deviation of the number of distinct values among attributes of the nominal type.
0.21
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
40.14
Average number of distinct values among the attributes of the nominal type.
1.12
First quartile of standard deviation of attributes of the numeric type.
0.81
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.21
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
0.75
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
0.95
Mean skewness among attributes of the numeric type.
1.28
Second quartile (Median) of entropy among attributes.
0.23
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.58
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
0.24
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
57.81
Percentage of instances belonging to the most frequent class.
516.33
Mean standard deviation of attributes of the numeric type.
0.38
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.53
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.98
Entropy of the target attribute values.
0.51
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
578062
Number of instances belonging to the most frequent class.
0.02
Minimal entropy among attributes.
33.05
Second quartile (Median) of means among attributes of the numeric type.
0.81
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.59
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
8.74
Maximum entropy among attributes.
-1.73
Minimum kurtosis among attributes of the numeric type.
0.01
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
0.4
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
99.11
Maximum kurtosis among attributes of the numeric type.
0.05
Minimum of means among attributes of the numeric type.

16 tasks

20 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: band_type
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: band_type
0 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: band_type
0 runs - estimation_procedure: 10-fold Learning Curve - evaluation_measure: predictive_accuracy - target_feature: band_type
45 runs - estimation_procedure: Interleaved Test then Train - target_feature: band_type
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
Define a new task