583
Number of instances (rows) of the dataset.
11
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.
9
Number of numeric attributes.
2
Number of nominal attributes.
2
Number of binary attributes.
0
First quartile of mutual information between the nominal attributes and the target attribute.
0.61
Average class difference between consecutive instances.
0.29
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
0.13
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
3.28
Mean skewness among attributes of the numeric type.
-0.04
First quartile of skewness among attributes of the numeric type.
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.71
The predictive accuracy obtained by always predicting the majority class.
82.43
Mean standard deviation of attributes of the numeric type.
0.94
First quartile of standard deviation of attributes of the numeric type.
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.02
Number of attributes divided by the number of instances.
149.36
Maximum kurtosis among attributes of the numeric type.
0.8
Minimal entropy among attributes.
0.8
Second quartile (Median) of entropy among attributes.
0.29
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
181.13
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
0
Standard deviation of the number of distinct values among attributes of the nominal type.
290.58
Maximum of means among attributes of the numeric type.
11.22
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.63
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
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
0.6
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0
Maximum mutual information between the nominal attributes and the target attribute.
-0.57
Minimum kurtosis among attributes of the numeric type.
6.48
Second quartile (Median) of means among attributes of the numeric type.
0.29
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
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.29
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
0.37
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
2
The maximum number of distinct values among attributes of the nominal type.
0.95
Minimum of means among attributes of the numeric type.
0
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0
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
0.29
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
0.17
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
10.51
Maximum skewness among attributes of the numeric type.
0
Minimal mutual information between the nominal attributes and the target attribute.
3.2
Second quartile (Median) of skewness among attributes of the numeric type.
0.7
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
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
288.92
Maximum standard deviation of attributes of the numeric type.
2
The minimal number of distinct values among attributes of the nominal type.
18.18
Percentage of binary attributes.
6.21
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.44
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
0.65
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.29
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0.8
Average entropy of the attributes.
-0.28
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
0.8
Third quartile of entropy among attributes.
0.23
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
0.29
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0.32
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
43.41
Third quartile of kurtosis among attributes of the numeric type.
0.57
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
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
0.29
Percentage of instances belonging to the least frequent class.
81.82
Percentage of numeric attributes.
95.31
Third quartile of means among attributes of the numeric type.
0.35
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
0.69
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.29
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
29.72
Mean kurtosis among attributes of the numeric type.
167
Number of instances belonging to the least frequent class.
18.18
Percentage of nominal attributes.
0
Third quartile of mutual information between the nominal attributes and the target attribute.
0.15
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
0.29
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
60.14
Mean of means among attributes of the numeric type.
0.72
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.8
First quartile of entropy among attributes.
5.71
Third quartile of skewness among attributes of the numeric type.
0.86
Entropy of the target attribute values.
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
71.36
Percentage of instances belonging to the most frequent class.
0
Average mutual information between the nominal attributes and the target attribute.
0.44
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
-0.09
First quartile of kurtosis among attributes of the numeric type.
212.78
Third quartile of standard deviation of attributes of the numeric type.
0.63
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
0.7
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
416
Number of instances belonging to the most frequent class.
166.89
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
0.24
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
2.31
First quartile of means among attributes of the numeric type.
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.29
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
0.32
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.8
Maximum entropy among attributes.
2
Average number of distinct values among the attributes of the nominal type.