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LED-display-domain-7digit

LED-display-domain-7digit

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  • artificial keel OpenML100 study_123 study_135 study_14 study_50 study_52 study_76 study_88 uci study_225 study_293
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Author: Breiman,L., Friedman,J.H., Olshen,R.A., and Stone,C.J. Source: [UCI](http://archive.ics.uci.edu/ml/datasets/LED+Display+Domain), [KEEL](http://sci2s.ugr.es/keel/dataset.php?cod=63, https://archive.ics.uci.edu/ml/datasets/LED+Display+Domain) - 1988 Please cite: [UCI](https://archive.ics.uci.edu/ml/citation_policy.html) LED display data set This simple domain contains 7 Boolean attributes and 10 classes, the set of decimal digits. Recall that LED displays contain 7 light-emitting diodes -- hence the reason for 7 attributes. The class attribute is an integer ranging between 0 and 9 inclusive, representing the possible digits show on the display. The problem would be easy if not for the introduction of noise. In this case, each attribute value has the 10% probability of having its value inverted. It's valuable to know the optimal Bayes rate for these databases. In this case, the misclassification rate is 26% (74% classification accuracy). ### Attribute Information * V1-V7 represent each of the 7 LEDs, with values either 0 or 1, according to whether the corresponding light is on or not for the decimal digit. Each has a 10% percent chance of being inverted.

8 features

Class (target)nominal10 unique values
0 missing
V1numeric2 unique values
0 missing
V2numeric2 unique values
0 missing
V3numeric2 unique values
0 missing
V4numeric2 unique values
0 missing
V5numeric2 unique values
0 missing
V6numeric2 unique values
0 missing
V7numeric2 unique values
0 missing
Show all 8 features

62 properties

NumberOfInstances
500
Number of instances (rows) of the dataset.
NumberOfFeatures
8
Number of attributes (columns) of the dataset.
NumberOfClasses
10
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
7
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
0
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
PercentageOfMissingValues
0
Percentage of missing values.
PercentageOfNumericFeatures
87.5
Percentage of numeric attributes.
PercentageOfSymbolicFeatures
12.5
Percentage of nominal attributes.
Quartile1AttributeEntropy
First quartile of entropy among attributes.
Quartile1KurtosisOfNumericAtts
-1.83
First quartile of kurtosis among attributes of the numeric type.
Quartile1MeansOfNumericAtts
0.59
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
-1.06
First quartile of skewness among attributes of the numeric type.
Quartile1StdDevOfNumericAtts
0.44
First quartile of standard deviation of attributes of the numeric type.
Quartile2AttributeEntropy
Second quartile (Median) of entropy among attributes.
Quartile2KurtosisOfNumericAtts
-1.48
Second quartile (Median) of kurtosis among attributes of the numeric type.
Quartile2MeansOfNumericAtts
0.67
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
-0.73
Second quartile (Median) of skewness among attributes of the numeric type.
Quartile2StdDevOfNumericAtts
0.47
Second quartile (Median) of standard deviation of attributes of the numeric type.
Quartile3AttributeEntropy
Third quartile of entropy among attributes.
Quartile3KurtosisOfNumericAtts
-0.87
Third quartile of kurtosis among attributes of the numeric type.
Quartile3MeansOfNumericAtts
0.73
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
-0.37
Third quartile of skewness among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
0.49
Third quartile of standard deviation of attributes of the numeric type.
AutoCorrelation
0.72
Average class difference between consecutive instances.
MeanMeansOfNumericAtts
0.66
Mean of means among attributes of the numeric type.
ClassEntropy
3.31
Entropy of the target attribute values.
Dimensionality
0.02
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
11.4
Percentage of instances belonging to the most frequent class.
MajorityClassSize
57
Number of instances belonging to the most frequent class.
MaxAttributeEntropy
Maximum entropy among attributes.
MaxKurtosisOfNumericAtts
0.74
Maximum kurtosis among attributes of the numeric type.
MaxMeansOfNumericAtts
0.82
Maximum of means among attributes of the numeric type.
MaxMutualInformation
Maximum mutual information between the nominal attributes and the target attribute.
MaxNominalAttDistinctValues
10
The maximum number of distinct values among attributes of the nominal type.
MaxSkewnessOfNumericAtts
0.43
Maximum skewness among attributes of the numeric type.
MaxStdDevOfNumericAtts
0.49
Maximum standard deviation of attributes of the numeric type.
MeanAttributeEntropy
Average entropy of the attributes.
MeanKurtosisOfNumericAtts
-1.12
Mean kurtosis among attributes of the numeric type.
NumberOfBinaryFeatures
0
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
10
Average number of distinct values among the attributes of the nominal type.
MeanSkewnessOfNumericAtts
-0.73
Mean skewness among attributes of the numeric type.
MeanStdDevOfNumericAtts
0.46
Mean standard deviation of attributes of the numeric type.
MinAttributeEntropy
Minimal entropy among attributes.
MinKurtosisOfNumericAtts
-1.87
Minimum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
0.4
Minimum of means among attributes of the numeric type.
MinMutualInformation
Minimal mutual information between the nominal attributes and the target attribute.
MinNominalAttDistinctValues
10
The minimal number of distinct values among attributes of the nominal type.
MinSkewnessOfNumericAtts
-1.65
Minimum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
0.39
Minimum standard deviation of attributes of the numeric type.
MinorityClassPercentage
7.4
Percentage of instances belonging to the least frequent class.
MinorityClassSize
37
Number of instances belonging to the least frequent class.
Show all 62 properties

18 tasks

Supervised Classification on LED-display-domain-7digit
13128 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: Class
Supervised Classification on LED-display-domain-7digit
31 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: Class
Supervised Classification on LED-display-domain-7digit
1 runs - estimation_procedure: 5 times 2-fold Crossvalidation - target_feature: Class
Supervised Classification on LED-display-domain-7digit
0 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: Class
Supervised Classification on LED-display-domain-7digit
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - target_feature: Class
Learning Curve on LED-display-domain-7digit
0 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: Class
Clustering on LED-display-domain-7digit
0 runs - estimation_procedure: 50 times Clustering
Clustering on LED-display-domain-7digit
0 runs - target_feature: Class
Clustering on LED-display-domain-7digit
0 runs
Clustering on LED-display-domain-7digit
0 runs - estimation_procedure: 50 times Clustering
Clustering on LED-display-domain-7digit
0 runs - estimation_procedure: 50 times Clustering
Clustering on LED-display-domain-7digit
0 runs - estimation_procedure: 50 times Clustering
Clustering on LED-display-domain-7digit
0 runs - estimation_procedure: 50 times Clustering
Clustering on LED-display-domain-7digit
0 runs - estimation_procedure: 50 times Clustering
Clustering on LED-display-domain-7digit
0 runs - estimation_procedure: 50 times Clustering
Clustering on LED-display-domain-7digit
0 runs - estimation_procedure: 50 times Clustering
Clustering on LED-display-domain-7digit
0 runs - estimation_procedure: 50 times Clustering
Clustering on LED-display-domain-7digit
0 runs - estimation_procedure: 50 times Clustering
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