Data
CostaMadre1

CostaMadre1

active ARFF Publicly available Visibility: public Uploaded 19-05-2015 by Hans Bauer
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Author: Hans Bauer Jesus","Deter Bergman Source: Unknown - Date unknown Please cite: Costa madre 1

38 features

def (target)nominal2 unique values
0 missing
anumeric53 unique values
0 missing
bnumeric35 unique values
0 missing
cnumeric18 unique values
0 missing
dnumeric29 unique values
0 missing
enumeric60 unique values
0 missing
fnumeric37 unique values
0 missing
gnumeric28 unique values
0 missing
hnumeric31 unique values
0 missing
inumeric22 unique values
0 missing
jnumeric31 unique values
0 missing
knumeric24 unique values
0 missing
lnumeric47 unique values
0 missing
mnumeric75 unique values
0 missing
nnumeric15 unique values
0 missing
onumeric32 unique values
0 missing
pnumeric89 unique values
0 missing
rnumeric11 unique values
0 missing
snumeric283 unique values
0 missing
tnumeric258 unique values
0 missing
unumeric294 unique values
0 missing
vnumeric93 unique values
0 missing
znumeric191 unique values
0 missing
aanumeric24 unique values
0 missing
abnumeric294 unique values
0 missing
acnumeric283 unique values
0 missing
adnumeric48 unique values
0 missing
aenumeric23 unique values
0 missing
afnumeric37 unique values
0 missing
agnumeric65 unique values
0 missing
ahnumeric29 unique values
0 missing
ainumeric133 unique values
0 missing
ajnumeric154 unique values
0 missing
aknumeric83 unique values
0 missing
alnumeric39 unique values
0 missing
amnumeric129 unique values
0 missing
annumeric201 unique values
0 missing
apnumeric92 unique values
0 missing

107 properties

296
Number of instances (rows) of the dataset.
38
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.
37
Number of numeric attributes.
1
Number of nominal attributes.
4061.63
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
0.13
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
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
0.22
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
87.16
Percentage of instances belonging to the most frequent class.
Minimal entropy among attributes.
21.41
Second quartile (Median) of kurtosis among attributes of the numeric type.
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.55
Entropy of the target attribute values.
0.09
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
258
Number of instances belonging to the most frequent class.
-1.12
Minimum kurtosis among attributes of the numeric type.
14.83
Second quartile (Median) of means among attributes of the numeric type.
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.71
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum entropy among attributes.
0.08
Minimum of means among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.13
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.13
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
163.9
Maximum kurtosis among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
3.6
Second quartile (Median) of skewness among attributes of the numeric type.
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
40743.96
Maximum of means among attributes of the numeric type.
2
The minimal number of distinct values among attributes of the nominal type.
2.63
Percentage of binary attributes.
13.85
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.56
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.13
Number of attributes divided by the number of instances.
Maximum mutual information between the nominal attributes and the target attribute.
-0.48
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
0.2
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
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.
0.06
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
36.62
Third quartile of kurtosis among attributes of the numeric type.
0.79
Average class difference between consecutive instances.
0.12
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.72
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
11.55
Maximum skewness among attributes of the numeric type.
12.84
Percentage of instances belonging to the least frequent class.
97.37
Percentage of numeric attributes.
39.64
Third quartile of means among attributes of the numeric type.
0.58
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
0.56
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.18
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
139977.24
Maximum standard deviation of attributes of the numeric type.
38
Number of instances belonging to the least frequent class.
2.63
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
0.18
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
0.2
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.25
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Average entropy of the attributes.
0.66
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of entropy among attributes.
4.69
Third quartile of skewness among attributes of the numeric type.
0.15
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
0.12
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.72
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
29.66
Mean kurtosis among attributes of the numeric type.
0.25
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
8.73
First quartile of kurtosis among attributes of the numeric type.
38.13
Third quartile of standard deviation of attributes of the numeric type.
0.58
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
0.56
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.18
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
1214.3
Mean of means among attributes of the numeric type.
0.15
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
2.47
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
0.18
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
0.2
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.25
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Average mutual information between the nominal attributes and the target attribute.
1
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
0.13
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.15
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
0.12
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.72
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
2
Average number of distinct values among the attributes of the nominal type.
2.31
First quartile of skewness among attributes of the numeric type.
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.58
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.
0.18
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
3.81
Mean skewness among attributes of the numeric type.
2.67
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
0.18
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
0.55
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.25
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001

8 tasks

88 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: def
1 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: matthews_correlation_coefficient - target_feature: def
1 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: def
0 runs - estimation_procedure: 33% Holdout set - target_feature: def
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
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