Data
eeg-eye-state

eeg-eye-state

active ARFF Publicly available Visibility: public Uploaded 22-05-2015 by Rafael G. Mantovani
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  • brain EEG OpenML100 study_123 study_14 study_34 study_7 time_series uci
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Author: Oliver Roesler Source: [UCI](https://archive.ics.uci.edu/ml/datasets/EEG+Eye+State), Baden-Wuerttemberg, Cooperative State University (DHBW), Stuttgart, Germany Please cite: [UCI](https://archive.ics.uci.edu/ml/citation_policy.html) 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 analyzing 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. The features correspond to 14 EEG measurements from the headset, originally labeled AF3, F7, F3, FC5, T7, P, O1, O2, P8, T8, FC6, F4, F8, AF4, in that order.

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

62 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.
55.12
Percentage of instances belonging to the most frequent class.
1767.29
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
8257
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
84.61
Second quartile (Median) of skewness among attributes of the numeric type.
Maximum entropy among attributes.
2056.52
Minimum kurtosis among attributes of the numeric type.
6.67
Percentage of binary attributes.
627.16
Second quartile (Median) of standard deviation of attributes of the numeric type.
Third quartile of entropy among attributes.
14979.18
Maximum kurtosis among attributes of the numeric type.
4009.77
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
14971.65
Third quartile of kurtosis among attributes of the numeric type.
4644.02
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of missing values.
4466.13
Third quartile of means among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
2
The minimal number of distinct values among attributes of the nominal type.
93.33
Percentage of numeric attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
2
The maximum number of distinct values among attributes of the nominal type.
-13.62
Minimum skewness among attributes of the numeric type.
6.67
Percentage of nominal attributes.
122.34
Third quartile of skewness among attributes of the numeric type.
122.39
Maximum skewness among attributes of the numeric type.
29.29
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
3343.82
Third quartile of standard deviation of attributes of the numeric type.
5891.29
Maximum standard deviation of attributes of the numeric type.
44.88
Percentage of instances belonging to the least frequent class.
2713.56
First quartile of kurtosis among attributes of the numeric type.
0
Standard deviation of the number of distinct values among attributes of the nominal type.
Average entropy of the attributes.
6723
Number of instances belonging to the least frequent class.
4193.08
First quartile of means among attributes of the numeric type.
8904.72
Mean kurtosis among attributes of the numeric type.
1
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
4316.88
Mean of means among attributes of the numeric type.
22.48
First quartile of skewness among attributes of the numeric type.
1
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
37.98
First quartile of standard deviation of attributes of the numeric type.
0.99
Entropy of the target attribute values.
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
Second quartile (Median) of entropy among attributes.
0
Number of attributes divided by the number of instances.
2
Average number of distinct values among the attributes of the nominal type.
9352.7
Second quartile (Median) of kurtosis among attributes of the numeric type.
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
71.74
Mean skewness among attributes of the numeric type.
4271.63
Second quartile (Median) of means among attributes of the numeric type.

16 tasks

95202 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: Class
67157 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: Class
0 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: Class
45 runs - estimation_procedure: 10-fold Learning Curve - target_feature: Class
0 runs - estimation_procedure: 50 times Clustering
0 runs - target_feature: Class
0 runs - estimation_procedure: 50 times Clustering
1303 runs - target_feature: Class
1301 runs - target_feature: Class
0 runs - target_feature: Class
0 runs - target_feature: Class
0 runs - target_feature: Class
0 runs - target_feature: Class
0 runs - target_feature: Class
0 runs - target_feature: Class
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