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active ARFF Publicly available Visibility: public Uploaded 07-10-2014 by Joaquin Vanschoren
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  • mythbusting_1 study_1 study_123 study_15 study_20 study_52 study_7 study_88 trivial
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Author: Source: Unknown - Date unknown Please cite: Dataset from the MLRR repository: http://axon.cs.byu.edu:5000/

12 features

class (target)nominal2 unique values
0 missing
ID (row identifier)numeric294 unique values
0 missing
lengthnumeric16 unique values
0 missing
even_oddnominal2 unique values
0 missing
first_char_vowelnominal2 unique values
0 missing
second_char_vowelnominal2 unique values
0 missing
vowelsnumeric9 unique values
0 missing
consonantsnumeric12 unique values
0 missing
vowel_consonant_rationumeric40 unique values
0 missing
spacesnumeric3 unique values
0 missing
dotsnumeric3 unique values
0 missing
wordsnumeric3 unique values
0 missing

107 properties

294
Number of instances (rows) of the dataset.
12
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.
8
Number of numeric attributes.
4
Number of nominal attributes.
0.85
Average class difference between consecutive instances.
1
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
1
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
1.62
Maximum skewness among attributes of the numeric type.
0.22
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
1.08
Third quartile of kurtosis among attributes of the numeric type.
1
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
1
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
2.86
Maximum standard deviation of attributes of the numeric type.
28.57
Percentage of instances belonging to the least frequent class.
66.67
Percentage of numeric attributes.
7.91
Third quartile of means among attributes of the numeric type.
0
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
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
1
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
0.77
Average entropy of the attributes.
84
Number of instances belonging to the least frequent class.
33.33
Percentage of nominal attributes.
0.86
Third quartile of mutual information between the nominal attributes and the target attribute.
1
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
1
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
1
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
1.16
Mean kurtosis among attributes of the numeric type.
1
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.44
First quartile of entropy among attributes.
1.55
Third quartile of skewness among attributes of the numeric type.
1.86
Third quartile of standard deviation of attributes of the numeric type.
1
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
1
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
4.42
Mean of means among attributes of the numeric type.
0.01
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.42
First quartile of kurtosis among attributes of the numeric type.
1
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0
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
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
1
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0.33
Average mutual information between the nominal attributes and the target attribute.
0.98
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.61
First quartile of means among attributes of the numeric type.
0
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
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
1
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
1
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
1.34
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
First quartile of mutual information between the nominal attributes and the target attribute.
1
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
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
0
Standard deviation of the number of distinct values among attributes of the nominal type.
0
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.
0.4
First quartile of skewness among attributes of the numeric type.
1
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0
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
1
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
1
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
1.04
Mean skewness among attributes of the numeric type.
0.44
First quartile of standard deviation of attributes of the numeric type.
0
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
1
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
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
71.43
Percentage of instances belonging to the most frequent class.
1.1
Mean standard deviation of attributes of the numeric type.
0.86
Second quartile (Median) of entropy among attributes.
1
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.86
Entropy of the target attribute values.
1
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
210
Number of instances belonging to the most frequent class.
0.44
Minimal entropy among attributes.
0.67
Second quartile (Median) of kurtosis among attributes of the numeric type.
1
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
1
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
1
Maximum entropy among attributes.
0.17
Minimum kurtosis among attributes of the numeric type.
2.26
Second quartile (Median) of means among attributes of the numeric type.
0
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
4.52
Maximum kurtosis among attributes of the numeric type.
0.23
Minimum of means among attributes of the numeric type.
0.12
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
1
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
1
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
14.03
Maximum of means among attributes of the numeric type.
0
Minimal mutual information between the nominal attributes and the target attribute.
1.35
Second quartile (Median) of skewness among attributes of the numeric type.
1
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.04
Number of attributes divided by the number of instances.
0.86
Maximum mutual information between the nominal attributes and the target attribute.
2
The minimal number of distinct values among attributes of the nominal type.
33.33
Percentage of binary attributes.
0.45
Second quartile (Median) of standard deviation of attributes of the numeric type.
0
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
2.63
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.
0.34
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
1
Third quartile of entropy among attributes.

14 tasks

146 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
33 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: precision - target_feature: class
1 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - 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
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: class
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
Define a new task