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pol

pol

active ARFF Publicly available Visibility: public Uploaded 23-04-2014 by Jan van Rijn
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  • study_3029 study_3419 study_5093 study_10740 study_10848 study_13427 study_15703 study_16218 study_122 study_4067 study_4992 study_1183 study_3442 study_4693 study_5182 study_11552 study_14120 study_18995 study_422 study_2681 study_12570 study_13008 study_18290 study_19354 study_1256 study_2308 study_754 study_927 study_6786 study_7240 study_11266 study_666 study_2056 study_3029 study_7101 study_13986 study_16032 study_17352 study_18925
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Author: Source: Unknown - Please cite: This is a commercial application described in Weiss & Indurkhya (1995). The data describes a telecommunication problem. No further information is available. Characteristics: (10000+5000) cases, 49 continuous attributes Source: collection of regression datasets by Luis Torgo (ltorgo@ncc.up.pt) at http://www.ncc.up.pt/~ltorgo/Regression/DataSets.html Original Source: The data in the original format can be obtained from http://www.cs.su.oz.au/~nitin

49 features

foo (target)numeric11 unique values
0 missing
f1numeric1 unique values
0 missing
f2numeric1 unique values
0 missing
f3numeric1 unique values
0 missing
f4numeric1 unique values
0 missing
f5numeric184 unique values
0 missing
f6numeric118 unique values
0 missing
f7numeric114 unique values
0 missing
f8numeric106 unique values
0 missing
f9numeric80 unique values
0 missing
f10numeric1 unique values
0 missing
f11numeric1 unique values
0 missing
f12numeric1 unique values
0 missing
f13numeric97 unique values
0 missing
f14numeric117 unique values
0 missing
f15numeric121 unique values
0 missing
f16numeric120 unique values
0 missing
f17numeric120 unique values
0 missing
f18numeric123 unique values
0 missing
f19numeric102 unique values
0 missing
f20numeric86 unique values
0 missing
f21numeric85 unique values
0 missing
f22numeric88 unique values
0 missing
f23numeric79 unique values
0 missing
f24numeric63 unique values
0 missing
f25numeric68 unique values
0 missing
f26numeric68 unique values
0 missing
f27numeric65 unique values
0 missing
f28numeric64 unique values
0 missing
f29numeric62 unique values
0 missing
f30numeric44 unique values
0 missing
f31numeric43 unique values
0 missing
f32numeric42 unique values
0 missing
f33numeric38 unique values
0 missing
f34numeric1 unique values
0 missing
f35numeric1 unique values
0 missing
f36numeric1 unique values
0 missing
f37numeric1 unique values
0 missing
f38numeric1 unique values
0 missing
f39numeric1 unique values
0 missing
f40numeric1 unique values
0 missing
f41numeric1 unique values
0 missing
f42numeric1 unique values
0 missing
f43numeric1 unique values
0 missing
f44numeric1 unique values
0 missing
f45numeric1 unique values
0 missing
f46numeric1 unique values
0 missing
f47numeric1 unique values
0 missing
f48numeric1 unique values
0 missing

107 properties

15000
Number of instances (rows) of the dataset.
49
Number of attributes (columns) of the dataset.
0
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.
49
Number of numeric attributes.
0
Number of nominal attributes.
14.54
Second quartile (Median) of kurtosis among attributes of the numeric type.
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
Entropy of the target attribute values.
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
0.94
Second quartile (Median) of means among attributes of the numeric type.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum entropy among attributes.
-0.99
Minimum kurtosis among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
147.26
Maximum kurtosis among attributes of the numeric type.
0
Minimum of means among attributes of the numeric type.
3.67
Second quartile (Median) of skewness among attributes of the numeric type.
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
110
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
3.15
Second quartile (Median) of standard deviation of attributes of the numeric type.
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.
The minimal number of distinct values among attributes of the nominal type.
0
Percentage of binary attributes.
Third quartile of entropy among attributes.
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.
The maximum number of distinct values among attributes of the nominal type.
0.31
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
69.44
Third quartile of kurtosis among attributes of the numeric type.
-39.42
Average class difference between consecutive instances.
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
11.62
Maximum skewness among attributes of the numeric type.
0
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
12.1
Third quartile of means among attributes of the numeric type.
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
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
41.73
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
100
Percentage of numeric attributes.
0
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
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
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Average entropy of the attributes.
Number of instances belonging to the least frequent class.
First quartile of entropy among attributes.
7.78
Third quartile of skewness among attributes of the numeric type.
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
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
33.56
Mean kurtosis among attributes of the numeric type.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
3.33
First quartile of kurtosis among attributes of the numeric type.
12.46
Third quartile of standard deviation of attributes of the numeric type.
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
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
19.63
Mean of means among attributes of the numeric type.
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0
First quartile of means among attributes of the numeric type.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
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
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Average mutual information between the nominal attributes and the target attribute.
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of mutual information between the nominal attributes and the target attribute.
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
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
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
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.
1.86
First quartile of skewness among attributes of the numeric type.
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
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
Standard deviation of the number of distinct values among attributes of the nominal type.
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
Average number of distinct values among the attributes of the nominal type.
0
First quartile of standard deviation of attributes of the numeric type.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
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
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
4.64
Mean skewness among attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
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
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
Percentage of instances belonging to the most frequent class.
7.24
Mean standard deviation of attributes of the numeric type.

7 tasks

0 runs - estimation_procedure: 10% Holdout set - target_feature: foo
0 runs - estimation_procedure: 5 times 2-fold Crossvalidation - target_feature: foo
0 runs - estimation_procedure: 33% Holdout set - target_feature: foo
0 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: foo
0 runs - estimation_procedure: Test on Training Data - target_feature: foo
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - target_feature: foo
0 runs - estimation_procedure: Leave one out - target_feature: foo
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