Data
bank32nh

bank32nh

active ARFF Publicly available Visibility: public Uploaded 04-10-2014 by Joaquin Vanschoren
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  • binarized_regression_problem mythbusting_1 study_1 study_15 study_20 study_41 study_7
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Author: Source: Unknown - Date unknown Please cite: Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a lower target value as positive ('P') and all others as negative ('N').

33 features

binaryClass (target)nominal2 unique values
0 missing
a1cxnumeric8173 unique values
0 missing
a1cynumeric8176 unique values
0 missing
a1sxnumeric8177 unique values
0 missing
a1synumeric8173 unique values
0 missing
a1rhonumeric8162 unique values
0 missing
a1popnumeric8188 unique values
0 missing
a2cxnumeric8176 unique values
0 missing
a2cynumeric8175 unique values
0 missing
a2sxnumeric8172 unique values
0 missing
a2synumeric8174 unique values
0 missing
a2rhonumeric8161 unique values
0 missing
a2popnumeric8185 unique values
0 missing
a3cxnumeric8173 unique values
0 missing
a3cynumeric8180 unique values
0 missing
a3sxnumeric8178 unique values
0 missing
a3synumeric8175 unique values
0 missing
a3rhonumeric8161 unique values
0 missing
a3popnumeric8187 unique values
0 missing
tempnumeric8159 unique values
0 missing
b1xnumeric8175 unique values
0 missing
b1ynumeric8170 unique values
0 missing
b1callnumeric7 unique values
0 missing
b1effnumeric8181 unique values
0 missing
b2xnumeric8175 unique values
0 missing
b2ynumeric8175 unique values
0 missing
b2callnumeric7 unique values
0 missing
b2effnumeric8174 unique values
0 missing
b3xnumeric8179 unique values
0 missing
b3ynumeric8173 unique values
0 missing
b3callnumeric7 unique values
0 missing
b3effnumeric8173 unique values
0 missing
mxqlnumeric5 unique values
0 missing

107 properties

8192
Number of instances (rows) of the dataset.
33
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.
32
Number of numeric attributes.
1
Number of nominal attributes.
0.86
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of entropy among attributes.
1.89
Third quartile of skewness among attributes of the numeric type.
0.49
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
0.33
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.69
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0.94
Mean kurtosis among attributes of the numeric type.
0.2
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
-1.2
First quartile of kurtosis among attributes of the numeric type.
1.02
Third quartile of standard deviation of attributes of the numeric type.
0.81
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
0.66
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.25
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
1.2
Mean of means among attributes of the numeric type.
0.5
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
-0
First quartile of means among attributes of the numeric type.
0.82
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
0.29
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.42
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Average mutual information between the nominal attributes and the target attribute.
1
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
0.22
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.49
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
0.33
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.69
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
-0
First quartile of skewness among attributes of the numeric type.
0.45
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.81
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.
0.25
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
2
Average number of distinct values among the attributes of the nominal type.
0.57
First quartile of standard deviation of attributes of the numeric type.
0.82
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
0.55
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.42
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
0.62
Mean skewness among attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
0.22
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.49
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
0.37
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
68.96
Percentage of instances belonging to the most frequent class.
0.97
Mean standard deviation of attributes of the numeric type.
-1.18
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.45
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.89
Entropy of the target attribute values.
0.1
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
5649
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
0.74
Second quartile (Median) of means among attributes of the numeric type.
0.82
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.68
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum entropy among attributes.
-1.31
Minimum kurtosis among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.22
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.25
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
8.89
Maximum kurtosis among attributes of the numeric type.
-0.02
Minimum of means among attributes of the numeric type.
0.01
Second quartile (Median) of skewness among attributes of the numeric type.
0.45
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.36
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
7
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
3.03
Percentage of binary attributes.
0.58
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.66
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.
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.
Third quartile of entropy among attributes.
0.29
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.
2
The maximum number of distinct values among attributes of the nominal type.
-0.02
Minimum skewness among attributes of the numeric type.
0
Percentage of missing values.
4.89
Third quartile of kurtosis among attributes of the numeric type.
0.57
Average class difference between consecutive instances.
0.33
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.69
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
2.23
Maximum skewness among attributes of the numeric type.
0.21
Minimum standard deviation of attributes of the numeric type.
96.97
Percentage of numeric attributes.
1.25
Third quartile of means among attributes of the numeric type.
0.81
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
0.66
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.25
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
3.2
Maximum standard deviation of attributes of the numeric type.
31.04
Percentage of instances belonging to the least frequent class.
3.03
Percentage of nominal attributes.
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
0.29
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.42
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Average entropy of the attributes.
2543
Number of instances belonging to the least frequent class.

7 tasks

544 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: binaryClass
200 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: binaryClass
0 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: binaryClass
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: binaryClass
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
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