DEVELOPMENT... OpenML
Data
EEGEyeState

EEGEyeState

in_preparation ARFF Publicly available Visibility: public Uploaded 02-10-2018 by Linda Watkins
0 likes downloaded by 0 people , 0 total downloads 0 issues 0 downvotes
Issue #Downvotes for this reason By


Loading wiki
Help us complete this description Edit
Description: All data is from one continuous EEG measurement with the Emotiv EEG Neuroheadset. The duration of the measurement was 117 seconds. The eye state was detected via a camera during the EEG measurement and added later manually to the file after analysing the video frames. '1' indicates the eye-closed and '0' the eye-open state. All values are in chronological order with the first measured value at the top of the data. Author: Oliver Roesler Oliver Roesler Source: [original](https://archive.ics.uci.edu/ml/datasets/EEG+Eye+State) - 2013-06-10 Please cite:

15 features

class (target)nominal2 unique values
0 missing
F1numeric545 unique values
0 missing
F2numeric443 unique values
0 missing
F3numeric332 unique values
0 missing
F4numeric312 unique values
0 missing
F5numeric285 unique values
0 missing
F6numeric330 unique values
0 missing
F7numeric290 unique values
0 missing
F8numeric292 unique values
0 missing
F9numeric303 unique values
0 missing
F10numeric345 unique values
0 missing
F11numeric415 unique values
0 missing
F12numeric341 unique values
0 missing
F13numeric555 unique values
0 missing
F14numeric589 unique values
0 missing
Show all 15 features

62 properties

NumberOfInstances
13495
Number of instances (rows) of the dataset.
NumberOfFeatures
15
Number of attributes (columns) of the dataset.
NumberOfClasses
2
Number of distinct values of the target attribute (if it is nominal).
NumberOfMissingValues
0
Number of missing values in the dataset.
NumberOfInstancesWithMissingValues
0
Number of instances with at least one value missing.
NumberOfNumericFeatures
14
Number of numeric attributes.
NumberOfSymbolicFeatures
1
Number of nominal attributes.
Quartile1MutualInformation
First quartile of mutual information between the nominal attributes and the target attribute.
PercentageOfBinaryFeatures
6.67
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
PercentageOfMissingValues
0
Percentage of missing values.
PercentageOfNumericFeatures
93.33
Percentage of numeric attributes.
PercentageOfSymbolicFeatures
6.67
Percentage of nominal attributes.
Quartile1AttributeEntropy
First quartile of entropy among attributes.
Quartile1KurtosisOfNumericAtts
2563.85
First quartile of kurtosis among attributes of the numeric type.
Quartile1MeansOfNumericAtts
4194.77
First quartile of means among attributes of the numeric type.
StdvNominalAttDistinctValues
0
Standard deviation of the number of distinct values among attributes of the nominal type.
Quartile1SkewnessOfNumericAtts
21.97
First quartile of skewness among attributes of the numeric type.
Quartile1StdDevOfNumericAtts
39.52
First quartile of standard deviation of attributes of the numeric type.
Quartile2AttributeEntropy
Second quartile (Median) of entropy among attributes.
Quartile2KurtosisOfNumericAtts
8507.91
Second quartile (Median) of kurtosis among attributes of the numeric type.
Quartile2MeansOfNumericAtts
4272.49
Second quartile (Median) of means among attributes of the numeric type.
Quartile2MutualInformation
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Quartile2SkewnessOfNumericAtts
81.03
Second quartile (Median) of skewness among attributes of the numeric type.
Quartile2StdDevOfNumericAtts
659.97
Second quartile (Median) of standard deviation of attributes of the numeric type.
Quartile3AttributeEntropy
Third quartile of entropy among attributes.
Quartile3KurtosisOfNumericAtts
13487.57
Third quartile of kurtosis among attributes of the numeric type.
Quartile3MeansOfNumericAtts
4471.95
Third quartile of means among attributes of the numeric type.
Quartile3MutualInformation
Third quartile of mutual information between the nominal attributes and the target attribute.
Quartile3SkewnessOfNumericAtts
116.12
Third quartile of skewness among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
3523
Third quartile of standard deviation of attributes of the numeric type.
AutoCorrelation
1
Average class difference between consecutive instances.
MeanMeansOfNumericAtts
4318.97
Mean of means among attributes of the numeric type.
ClassEntropy
1
Entropy of the target attribute values.
Dimensionality
0
Number of attributes divided by the number of instances.
EquivalentNumberOfAtts
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
MajorityClassPercentage
50.87
Percentage of instances belonging to the most frequent class.
MajorityClassSize
6865
Number of instances belonging to the most frequent class.
MaxAttributeEntropy
Maximum entropy among attributes.
MaxKurtosisOfNumericAtts
13494.29
Maximum kurtosis among attributes of the numeric type.
MaxMeansOfNumericAtts
4646.88
Maximum of means among attributes of the numeric type.
MaxMutualInformation
Maximum mutual information between the nominal attributes and the target attribute.
MaxNominalAttDistinctValues
2
The maximum number of distinct values among attributes of the nominal type.
MaxSkewnessOfNumericAtts
116.16
Maximum skewness among attributes of the numeric type.
MaxStdDevOfNumericAtts
6206.94
Maximum standard deviation of attributes of the numeric type.
MeanAttributeEntropy
Average entropy of the attributes.
MeanKurtosisOfNumericAtts
8095.46
Mean kurtosis among attributes of the numeric type.
NumberOfBinaryFeatures
1
Number of binary attributes.
MeanMutualInformation
Average mutual information between the nominal attributes and the target attribute.
MeanNoiseToSignalRatio
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
MeanNominalAttDistinctValues
2
Average number of distinct values among the attributes of the nominal type.
MeanSkewnessOfNumericAtts
68.59
Mean skewness among attributes of the numeric type.
MeanStdDevOfNumericAtts
1861.7
Mean standard deviation of attributes of the numeric type.
MinAttributeEntropy
Minimal entropy among attributes.
MinKurtosisOfNumericAtts
1940.62
Minimum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
4007.77
Minimum of means among attributes of the numeric type.
MinMutualInformation
Minimal mutual information between the nominal attributes and the target attribute.
MinNominalAttDistinctValues
2
The minimal number of distinct values among attributes of the nominal type.
MinSkewnessOfNumericAtts
-13.35
Minimum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
30.55
Minimum standard deviation of attributes of the numeric type.
MinorityClassPercentage
49.13
Percentage of instances belonging to the least frequent class.
MinorityClassSize
6630
Number of instances belonging to the least frequent class.
Show all 62 properties

15 tasks

Supervised Classification on EEGEyeState
0 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: class
Learning Curve on EEGEyeState
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on EEGEyeState
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on EEGEyeState
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on EEGEyeState
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Supervised Data Stream Classification on EEGEyeState
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: class
Clustering on EEGEyeState
0 runs - estimation_procedure: 50 times Clustering
Clustering on EEGEyeState
0 runs - estimation_procedure: 50 times Clustering
Clustering on EEGEyeState
0 runs - estimation_procedure: 50 times Clustering
Clustering on EEGEyeState
0 runs - estimation_procedure: 50 times Clustering
Clustering on EEGEyeState
0 runs - estimation_procedure: 50 times Clustering
Clustering on EEGEyeState
0 runs - estimation_procedure: 50 times Clustering
Clustering on EEGEyeState
0 runs - estimation_procedure: 50 times Clustering
Clustering on EEGEyeState
0 runs - estimation_procedure: 50 times Clustering
Clustering on EEGEyeState
0 runs - estimation_procedure: 50 times Clustering
Define a new task