Data
pokerhand

pokerhand

active ARFF Publicly available Visibility: public Uploaded 10-04-2014 by Jan van Rijn
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Author: Source: Unknown - Please cite: Normalized version of the pokerhand data set. Automated file upload of pokerhand-normalized.arff

11 features

class (target)nominal10 unique values
0 missing
s1nominal4 unique values
0 missing
r1numeric12 unique values
0 missing
s2nominal4 unique values
0 missing
r2numeric13 unique values
0 missing
s3nominal4 unique values
0 missing
r3numeric13 unique values
0 missing
s4nominal4 unique values
0 missing
r4numeric13 unique values
0 missing
s5nominal4 unique values
0 missing
r5numeric12 unique values
0 missing

107 properties

829201
Number of instances (rows) of the dataset.
11
Number of attributes (columns) of the dataset.
10
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.
5
Number of numeric attributes.
6
Number of nominal attributes.
238.95
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.
0
First quartile of mutual information between the nominal attributes and the target attribute.
0.01
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.62
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
0.84
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
5
Average number of distinct values among the attributes of the nominal type.
-0.84
First quartile of skewness among attributes of the numeric type.
0.98
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.84
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
2.45
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
0
Mean skewness among attributes of the numeric type.
1.74
First quartile of standard deviation of attributes of the numeric type.
1
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.2
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
0.74
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
2.07
Mean standard deviation of attributes of the numeric type.
2
Second quartile (Median) of entropy among attributes.
0.01
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.62
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
0.3
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
50.11
Percentage of instances belonging to the most frequent class.
1.99
Minimal entropy among attributes.
-0.36
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.98
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
1.42
Entropy of the target attribute values.
0.46
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
415526
Number of instances belonging to the most frequent class.
-0.65
Minimum kurtosis among attributes of the numeric type.
7
Second quartile (Median) of means among attributes of the numeric type.
1
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.54
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
2
Maximum entropy among attributes.
2.61
Minimum of means among attributes of the numeric type.
0.01
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.01
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.47
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
1.32
Maximum kurtosis among attributes of the numeric type.
0
Minimal mutual information between the nominal attributes and the target attribute.
0
Second quartile (Median) of skewness among attributes of the numeric type.
0.98
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.07
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
11.39
Maximum of means among attributes of the numeric type.
4
The minimal number of distinct values among attributes of the nominal type.
0
Percentage of binary attributes.
2.24
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.93
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.
0.01
Maximum mutual information between the nominal attributes and the target attribute.
-1.24
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
2
Third quartile of entropy among attributes.
0.09
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
170.31
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
10
The maximum number of distinct values among attributes of the nominal type.
1.74
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
1.3
Third quartile of kurtosis among attributes of the numeric type.
0.75
Average class difference between consecutive instances.
0.84
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
1.24
Maximum skewness among attributes of the numeric type.
0
Percentage of instances belonging to the least frequent class.
45.45
Percentage of numeric attributes.
10.3
Third quartile of means among attributes of the numeric type.
0.84
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
0.93
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
2.37
Maximum standard deviation of attributes of the numeric type.
2
Number of instances belonging to the least frequent class.
54.55
Percentage of nominal attributes.
0.01
Third quartile of mutual information between the nominal attributes and the target attribute.
0.2
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
0.09
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
2
Average entropy of the attributes.
0.72
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
1.99
First quartile of entropy among attributes.
0.85
Third quartile of skewness among attributes of the numeric type.
0.62
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
0.84
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
0.25
Mean kurtosis among attributes of the numeric type.
0.41
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
-0.51
First quartile of kurtosis among attributes of the numeric type.
2.31
Third quartile of standard deviation of attributes of the numeric type.
0.84
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
0.93
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
7
Mean of means among attributes of the numeric type.
0.01
Average mutual information between the nominal attributes and the target attribute.
0.24
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
3.7
First quartile of means among attributes of the numeric type.
1
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.2
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
0.09
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

13 tasks

20 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
4 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: class
2 runs - estimation_procedure: 5 times 2-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: precision - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - evaluation_measure: predictive_accuracy - 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
288 runs - estimation_procedure: Interleaved Test then Train - target_feature: class
Define a new task