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MindCave2

MindCave2

active ARFF Publicly available Visibility: public Uploaded 20-05-2015 by Hans Bauer
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Author: Source: Unknown - Date unknown Please cite: Mind Cave 2

40 features

def (target)nominal2 unique values
0 missing
anumeric35 unique values
0 missing
bnumeric30 unique values
0 missing
cnumeric13 unique values
0 missing
dnumeric16 unique values
0 missing
enumeric40 unique values
0 missing
fnumeric37 unique values
0 missing
gnumeric27 unique values
0 missing
hnumeric43 unique values
0 missing
inumeric22 unique values
0 missing
jnumeric25 unique values
0 missing
knumeric15 unique values
0 missing
lnumeric38 unique values
0 missing
mnumeric57 unique values
0 missing
nnumeric17 unique values
0 missing
onumeric30 unique values
0 missing
pnumeric65 unique values
0 missing
rnumeric6 unique values
0 missing
snumeric25 unique values
0 missing
tnumeric30 unique values
0 missing
unumeric123 unique values
0 missing
vnumeric118 unique values
0 missing
znumeric125 unique values
0 missing
aanumeric69 unique values
0 missing
abnumeric105 unique values
0 missing
acnumeric25 unique values
0 missing
adnumeric125 unique values
0 missing
aenumeric123 unique values
0 missing
afnumeric36 unique values
0 missing
agnumeric27 unique values
0 missing
ahnumeric36 unique values
0 missing
ainumeric52 unique values
0 missing
ajnumeric31 unique values
0 missing
aknumeric90 unique values
0 missing
alnumeric91 unique values
0 missing
amnumeric52 unique values
0 missing
annumeric30 unique values
0 missing
aonumeric79 unique values
0 missing
apnumeric86 unique values
0 missing
arnumeric69 unique values
0 missing

107 properties

125
Number of instances (rows) of the dataset.
40
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.
39
Number of numeric attributes.
1
Number of nominal attributes.
2.69
Second quartile (Median) of skewness among attributes of the numeric type.
0.04
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.11
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
65069.37
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
16.16
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.69
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.32
Number of attributes divided by the number of instances.
Maximum mutual information between the nominal attributes and the target attribute.
2
The minimal number of distinct values among attributes of the nominal type.
2.5
Percentage of binary attributes.
Third quartile of entropy among attributes.
0.3
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.
-1.37
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
10.29
Third quartile of kurtosis among attributes of the numeric type.
0.56
Average class difference between consecutive instances.
0.37
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.65
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
4.18
Maximum skewness among attributes of the numeric type.
0.09
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
35.45
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
0.69
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.33
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
154169.9
Maximum standard deviation of attributes of the numeric type.
35.2
Percentage of instances belonging to the least frequent class.
97.5
Percentage of numeric attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
0.3
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
0.3
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.27
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Average entropy of the attributes.
44
Number of instances belonging to the least frequent class.
2.5
Percentage of nominal attributes.
3.01
Third quartile of skewness among attributes of the numeric type.
0.21
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
0.37
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.65
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
7.54
Mean kurtosis among attributes of the numeric type.
0.67
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of entropy among attributes.
3.31
First quartile of kurtosis among attributes of the numeric type.
43.82
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
0.69
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.33
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
1814.85
Mean of means among attributes of the numeric type.
0.3
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
2.1
First quartile of means among attributes of the numeric type.
0.53
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.3
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
0.3
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.27
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Average mutual information between the nominal attributes and the target attribute.
0.26
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of mutual information between the nominal attributes and the target attribute.
0.38
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.21
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
0.37
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.65
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.
1
Number of binary attributes.
1.82
First quartile of skewness among attributes of the numeric type.
0.04
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.
0.33
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
2
Average number of distinct values among the attributes of the nominal type.
1.05
First quartile of standard deviation of attributes of the numeric type.
0.53
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.3
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
0.64
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.27
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
2.33
Mean skewness among attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
0.38
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.21
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
0.32
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
64.8
Percentage of instances belonging to the most frequent class.
4242.4
Mean standard deviation of attributes of the numeric type.
8.34
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.04
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.94
Entropy of the target attribute values.
0.27
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
81
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
13.74
Second quartile (Median) of means among attributes of the numeric type.
0.53
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.61
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum entropy among attributes.
-0.6
Minimum kurtosis among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.38
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.33
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
20.77
Maximum kurtosis among attributes of the numeric type.
0.08
Minimum of means among attributes of the numeric type.

11 tasks

0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
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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