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active ARFF Publicly available Visibility: public Uploaded 29-07-2016 by Rafael Gomes Mantovani
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41 features

Class (target)nominal11 unique values
0 missing
V1numeric861 unique values
0 missing
V2numeric979 unique values
0 missing
V3numeric1199 unique values
0 missing
V4numeric1072 unique values
0 missing
V5numeric1025 unique values
0 missing
V6numeric961 unique values
0 missing
V7numeric965 unique values
0 missing
V8numeric1003 unique values
0 missing
V9numeric1032 unique values
0 missing
V10numeric1234 unique values
0 missing
V11numeric861 unique values
0 missing
V12numeric894 unique values
0 missing
V13numeric1300 unique values
0 missing
V14numeric696 unique values
0 missing
V15numeric810 unique values
0 missing
V16numeric727 unique values
0 missing
V17numeric805 unique values
0 missing
V18numeric899 unique values
0 missing
V19numeric852 unique values
0 missing
V20numeric1282 unique values
0 missing
V21numeric861 unique values
0 missing
V22numeric990 unique values
0 missing
V23numeric1223 unique values
0 missing
V24numeric1150 unique values
0 missing
V25numeric1112 unique values
0 missing
V26numeric1100 unique values
0 missing
V27numeric1010 unique values
0 missing
V28numeric1082 unique values
0 missing
V29numeric1110 unique values
0 missing
V30numeric1217 unique values
0 missing
V31numeric861 unique values
0 missing
V32numeric898 unique values
0 missing
V33numeric1309 unique values
0 missing
V34numeric742 unique values
0 missing
V35numeric838 unique values
0 missing
V36numeric750 unique values
0 missing
V37numeric797 unique values
0 missing
V38numeric921 unique values
0 missing
V39numeric865 unique values
0 missing
V40numeric1252 unique values
0 missing

107 properties

5500
Number of instances (rows) of the dataset.
41
Number of attributes (columns) of the dataset.
11
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.
40
Number of numeric attributes.
1
Number of nominal attributes.
0.88
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.1
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
-0.24
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0.03
Second quartile (Median) of skewness among attributes of the numeric type.
0.94
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.01
Number of attributes divided by the number of instances.
Maximum mutual information between the nominal attributes and the target attribute.
11
The minimal number of distinct values among attributes of the nominal type.
0
Percentage of binary attributes.
0.22
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.11
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.
11
The maximum number of distinct values among attributes of the nominal type.
-1.14
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
0.88
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.96
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
2.67
Maximum skewness among attributes of the numeric type.
0.14
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
1.09
Third quartile of kurtosis among attributes of the numeric type.
1
Average class difference between consecutive instances.
0.94
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.08
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
0.35
Maximum standard deviation of attributes of the numeric type.
9.09
Percentage of instances belonging to the least frequent class.
97.56
Percentage of numeric attributes.
-0.49
Third quartile of means among attributes of the numeric type.
0.96
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
0.11
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.91
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Average entropy of the attributes.
500
Number of instances belonging to the least frequent class.
2.44
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
0.09
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
0.88
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.96
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
1.2
Mean kurtosis among attributes of the numeric type.
0.97
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of entropy among attributes.
0.52
Third quartile of skewness among attributes of the numeric type.
0.9
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
0.94
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.08
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
-0.61
Mean of means among attributes of the numeric type.
0.23
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
-0.62
First quartile of kurtosis among attributes of the numeric type.
0.25
Third quartile of standard deviation of attributes of the numeric type.
0.96
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
0.11
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.91
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Average mutual information between the nominal attributes and the target attribute.
0.75
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
-0.71
First quartile of means among attributes of the numeric type.
0.97
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.09
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
0.9
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
0.88
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.96
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
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
0.11
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.96
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.
0.08
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
11
Average number of distinct values among the attributes of the nominal type.
-0.29
First quartile of skewness among attributes of the numeric type.
0.88
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.09
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
0.99
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.91
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
0.29
Mean skewness among attributes of the numeric type.
0.2
First quartile of standard deviation of attributes of the numeric type.
0.97
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.9
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
0.02
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
9.09
Percentage of instances belonging to the most frequent class.
0.23
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
0.11
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.88
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
3.46
Entropy of the target attribute values.
0.98
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
500
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
0.03
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.97
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.74
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum entropy among attributes.
-1.08
Minimum kurtosis among attributes of the numeric type.
-0.58
Second quartile (Median) of means among attributes of the numeric type.
0.11
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.82
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
11.45
Maximum kurtosis among attributes of the numeric type.
-1.1
Minimum of means among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.

11 tasks

0 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: Class
0 runs - estimation_procedure: 5 times 2-fold Crossvalidation - target_feature: Class
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - target_feature: Class
0 runs - estimation_procedure: Leave one out - target_feature: Class
0 runs - estimation_procedure: 10% Holdout set - target_feature: Class
0 runs - estimation_procedure: 20% Holdout (Ordered) - target_feature: Class
0 runs - estimation_procedure: Test on Training Data - 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 times 10-fold Learning Curve - target_feature: Class
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: Class
Define a new task