101
Number of instances (rows) of the dataset.
18
Number of attributes (columns) of the dataset.
7
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.
1
Number of numeric attributes.
17
Number of nominal attributes.
19.51
Third quartile of standard deviation of attributes of the numeric type.
0.82
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
0.93
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
41
Number of instances belonging to the most frequent class.
0.55
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
0.04
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
-0.22
First quartile of kurtosis among attributes of the numeric type.
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.41
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
0.13
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.99
Maximum entropy among attributes.
2
Average number of distinct values among the attributes of the nominal type.
0.95
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.23
First quartile of means among attributes of the numeric type.
0.15
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.43
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
0.83
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
1.61
Mean skewness among attributes of the numeric type.
15
Number of binary attributes.
0.31
First quartile of mutual information between the nominal attributes and the target attribute.
0.35
Average class difference between consecutive instances.
0.8
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.41
The predictive accuracy obtained by always predicting the majority class.
37.52
Mean standard deviation of attributes of the numeric type.
-0.07
First quartile of skewness among attributes of the numeric type.
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.18
Number of attributes divided by the number of instances.
4811.61
Maximum kurtosis among attributes of the numeric type.
0.4
Minimal entropy among attributes.
0.91
First quartile of standard deviation of attributes of the numeric type.
0.15
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
4.55
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.
13207.13
Maximum of means among attributes of the numeric type.
0.82
Second quartile (Median) of entropy among attributes.
0.95
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
0.8
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
0.98
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.97
Maximum mutual information between the nominal attributes and the target attribute.
0.71
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.11
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
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.08
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
0.07
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
2
The maximum number of distinct values among attributes of the nominal type.
-1.99
Minimum kurtosis among attributes of the numeric type.
9.24
Second quartile (Median) of means among attributes of the numeric type.
0.5
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.86
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
0.15
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.9
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
0.91
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
67.4
Maximum skewness among attributes of the numeric type.
-23.5
Minimum of means among attributes of the numeric type.
0.48
Second quartile (Median) of skewness among attributes of the numeric type.
0.95
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
0.8
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
7947.07
Maximum standard deviation of attributes of the numeric type.
0.05
Minimal mutual information between the nominal attributes and the target attribute.
4.67
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.11
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
0.93
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.08
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0.81
Average entropy of the attributes.
2
The minimal number of distinct values among attributes of the nominal type.
83.33
Percentage of binary attributes.
0.98
Third quartile of entropy among attributes.
0.86
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
0.13
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.9
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
-21.17
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
7.97
Third quartile of kurtosis among attributes of the numeric type.
0.95
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
0.83
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
0
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
38.28
Third quartile of means among attributes of the numeric type.
0.11
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
0.93
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 .001
32.76
Mean kurtosis among attributes of the numeric type.
0.04
Percentage of instances belonging to the least frequent class.
5.56
Percentage of numeric attributes.
0.79
Third quartile of mutual information between the nominal attributes and the target attribute.
0.86
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
0.13
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.9
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
100.14
Mean of means among attributes of the numeric type.
4
Number of instances belonging to the least frequent class.
94.44
Percentage of nominal attributes.
1.97
Third quartile of skewness among attributes of the numeric type.
2.39
Entropy of the target attribute values.
0.83
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
40.59
Percentage of instances belonging to the most frequent class.
0.53
Average mutual information between the nominal attributes and the target attribute.
1
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.68
First quartile of entropy among attributes.