Data
BNG(eucalyptus)

BNG(eucalyptus)

active ARFF public domain Visibility: public Uploaded 12-11-2014 by Jan van Rijn
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20 features

Utility (target)nominal5 unique values
0 missing
Abbrevnominal16 unique values
0 missing
Repnumeric4 unique values
0 missing
Localitynominal8 unique values
0 missing
Map_Refnominal14 unique values
0 missing
Latitudenominal12 unique values
0 missing
Altitudenumeric385233 unique values
0 missing
Rainfallnumeric792836 unique values
0 missing
Frostsnumeric2 unique values
0 missing
Yearnumeric5 unique values
0 missing
Spnominal27 unique values
0 missing
PMCnonumeric999017 unique values
0 missing
DBHnumeric984086 unique values
0 missing
Htnumeric963295 unique values
0 missing
Survnumeric824123 unique values
0 missing
Vignumeric698079 unique values
0 missing
Ins_resnumeric586925 unique values
0 missing
Stem_Fmnumeric590899 unique values
0 missing
Crown_Fmnumeric715807 unique values
0 missing
Brnch_Fmnumeric555401 unique values
0 missing

107 properties

1000000
Number of instances (rows) of the dataset.
20
Number of attributes (columns) of the dataset.
5
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.
14
Number of numeric attributes.
6
Number of nominal attributes.
8.46
Mean kurtosis among attributes of the numeric type.
0.82
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
3.14
First quartile of entropy among attributes.
0.64
Third quartile of skewness among attributes of the numeric type.
0.42
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
0.4
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.81
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0.37
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
391.68
Mean of means among attributes of the numeric type.
0.49
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
-0.74
First quartile of kurtosis among attributes of the numeric type.
84.72
Third quartile of standard deviation of attributes of the numeric type.
0.75
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
0.72
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.53
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0.21
Average mutual information between the nominal attributes and the target attribute.
0.38
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
2.92
First quartile of means among attributes of the numeric type.
0.85
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.45
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
0.47
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.81
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
16.75
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.
0.14
First quartile of mutual information between the nominal attributes and the target attribute.
0.4
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.42
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
0.4
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
7.66
Standard deviation of the number of distinct values among attributes of the nominal type.
0.37
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
13.67
Average number of distinct values among the attributes of the nominal type.
-0.4
First quartile of skewness among attributes of the numeric type.
0.49
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.75
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
0.69
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.53
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
0.69
Mean skewness among attributes of the numeric type.
0.79
First quartile of standard deviation of attributes of the numeric type.
0.85
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.45
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
0.49
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
28.98
Percentage of instances belonging to the most frequent class.
175.47
Mean standard deviation of attributes of the numeric type.
3.66
Second quartile (Median) of entropy among attributes.
0.4
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.42
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
0.37
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
289779
Number of instances belonging to the most frequent class.
2.77
Minimal entropy among attributes.
-0.18
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.49
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
2.26
Entropy of the target attribute values.
4.55
Maximum entropy among attributes.
-1.96
Minimum kurtosis among attributes of the numeric type.
6.13
Second quartile (Median) of means among attributes of the numeric type.
0.85
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.58
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
111.65
Maximum kurtosis among attributes of the numeric type.
-2.55
Minimum of means among attributes of the numeric type.
0.17
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.4
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.63
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
2071.7
Maximum of means among attributes of the numeric type.
0.14
Minimal mutual information between the nominal attributes and the target attribute.
0.03
Second quartile (Median) of skewness among attributes of the numeric type.
0.49
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.12
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
0.36
Maximum mutual information between the nominal attributes and the target attribute.
5
The minimal number of distinct values among attributes of the nominal type.
0
Percentage of binary attributes.
1.8
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.72
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.
27
The maximum number of distinct values among attributes of the nominal type.
-0.6
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
4.18
Third quartile of entropy among attributes.
0.47
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
10.97
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
9.1
Maximum skewness among attributes of the numeric type.
0.5
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
0.36
Third quartile of kurtosis among attributes of the numeric type.
0.22
Average class difference between consecutive instances.
0.4
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.81
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
1576
Maximum standard deviation of attributes of the numeric type.
14.28
Percentage of instances belonging to the least frequent class.
70
Percentage of numeric attributes.
402.36
Third quartile of means among attributes of the numeric type.
0.75
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
0.72
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.37
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
3.66
Average entropy of the attributes.
142795
Number of instances belonging to the least frequent class.
30
Percentage of nominal attributes.
0.29
Third quartile of mutual information between the nominal attributes and the target attribute.
0.45
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
0.47
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.53
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001

3 tasks

117 runs - estimation_procedure: Interleaved Test then Train - target_feature: Utility
0 runs - estimation_procedure: 50 times Clustering
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