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eeg-eye-state

eeg-eye-state

active ARFF Publicly available Visibility: public Uploaded 22-05-2015 by Rafael Gomes Mantovani
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15 features

Class (target)nominal2 unique values
0 missing
V1numeric548 unique values
0 missing
V2numeric452 unique values
0 missing
V3numeric345 unique values
0 missing
V4numeric312 unique values
0 missing
V5numeric285 unique values
0 missing
V6numeric330 unique values
0 missing
V7numeric290 unique values
0 missing
V8numeric294 unique values
0 missing
V9numeric304 unique values
0 missing
V10numeric346 unique values
0 missing
V11numeric419 unique values
0 missing
V12numeric343 unique values
0 missing
V13numeric558 unique values
0 missing
V14numeric592 unique values
0 missing

107 properties

14980
Number of instances (rows) of the dataset.
15
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.
14
Number of numeric attributes.
1
Number of nominal attributes.
0.11
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
4193.08
First quartile of means among attributes of the numeric type.
0.86
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.23
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
0.19
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.62
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.
0.19
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.53
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
0.62
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.83
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.
22.48
First quartile of skewness among attributes of the numeric type.
0.61
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.82
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.
0.19
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.
37.98
First quartile of standard deviation of attributes of the numeric type.
0.86
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.23
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
0.83
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.62
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
71.74
Mean skewness among attributes of the numeric type.
1767.29
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
0.19
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.53
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
0.16
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
55.12
Percentage of instances belonging to the most frequent class.
Minimal entropy among attributes.
9352.7
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.61
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.99
Entropy of the target attribute values.
0.67
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
8257
Number of instances belonging to the most frequent class.
2056.52
Minimum kurtosis among attributes of the numeric type.
4271.63
Second quartile (Median) of means among attributes of the numeric type.
0.86
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.57
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum entropy among attributes.
4009.77
Minimum of means among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.19
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.41
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
14979.18
Maximum kurtosis among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
84.61
Second quartile (Median) of skewness among attributes of the numeric type.
0.61
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.13
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
4644.02
Maximum of means among attributes of the numeric type.
2
The minimal number of distinct values among attributes of the nominal type.
6.67
Percentage of binary attributes.
627.16
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.81
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.
Maximum mutual information between the nominal attributes and the target attribute.
-13.62
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
0.19
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.
29.29
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
14971.65
Third quartile of kurtosis among attributes of the numeric type.
1
Average class difference between consecutive instances.
0.62
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.83
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
122.39
Maximum skewness among attributes of the numeric type.
44.88
Percentage of instances belonging to the least frequent class.
93.33
Percentage of numeric attributes.
4466.13
Third quartile of means among attributes of the numeric type.
0.82
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
0.81
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.19
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
5891.29
Maximum standard deviation of attributes of the numeric type.
6723
Number of instances belonging to the least frequent class.
6.67
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
0.23
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
0.19
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.62
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Average entropy of the attributes.
0.54
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of entropy among attributes.
122.34
Third quartile of skewness among attributes of the numeric type.
0.53
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
0.62
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.83
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
8904.72
Mean kurtosis among attributes of the numeric type.
0.46
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
2713.56
First quartile of kurtosis among attributes of the numeric type.
3343.82
Third quartile of standard deviation of attributes of the numeric type.
0.82
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
0.81
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.19
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
4316.88
Mean of means among attributes of the numeric type.

11 tasks

720 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: Class
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - target_feature: Class
0 runs - estimation_procedure: Leave one out - target_feature: Class
0 runs - estimation_procedure: 5 times 2-fold Crossvalidation - target_feature: Class
0 runs - estimation_procedure: 33% Holdout set - target_feature: Class
0 runs - estimation_procedure: Test on Training Data - target_feature: Class
0 runs - estimation_procedure: 10% Holdout set - target_feature: Class
0 runs - estimation_procedure: 20% Holdout (Ordered) - target_feature: Class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: Class
0 runs - estimation_procedure: 10 times 10-fold Learning Curve - target_feature: Class
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: Class
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