Data
isolet

isolet

active ARFF Publicly available Visibility: public Uploaded 24-06-2019 by Julia Moosbauer
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Binarized version of the isolet dataset (see version 1). Only instances with class labels 1 and 2 from the original dataset are considered.

618 features

class (target)nominal2 unique values
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Show first 100 features

62 properties

NumberOfInstances
600
Number of instances (rows) of the dataset.
NumberOfFeatures
618
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
617
Number of numeric attributes.
NumberOfSymbolicFeatures
1
Number of nominal attributes.
ClassEntropy
1
Entropy of the target attribute values.
MeanNoiseToSignalRatio
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
Quartile2AttributeEntropy
Second quartile (Median) of entropy among attributes.
Dimensionality
1.03
Number of attributes divided by the number of instances.
MeanNominalAttDistinctValues
2
Average number of distinct values among the attributes of the nominal type.
Quartile2KurtosisOfNumericAtts
0.14
Second quartile (Median) of kurtosis among attributes of the numeric type.
EquivalentNumberOfAtts
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
MeanSkewnessOfNumericAtts
0.84
Mean skewness among attributes of the numeric type.
Quartile2MeansOfNumericAtts
0.25
Second quartile (Median) of means among attributes of the numeric type.
MajorityClassPercentage
50
Percentage of instances belonging to the most frequent class.
MeanStdDevOfNumericAtts
0.31
Mean standard deviation of attributes of the numeric type.
Quartile2MutualInformation
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
MajorityClassSize
300
Number of instances belonging to the most frequent class.
MinAttributeEntropy
Minimal entropy among attributes.
Quartile2SkewnessOfNumericAtts
-0.03
Second quartile (Median) of skewness among attributes of the numeric type.
MaxAttributeEntropy
Maximum entropy among attributes.
MinKurtosisOfNumericAtts
-1.38
Minimum kurtosis among attributes of the numeric type.
PercentageOfBinaryFeatures
0.16
Percentage of binary attributes.
Quartile2StdDevOfNumericAtts
0.3
Second quartile (Median) of standard deviation of attributes of the numeric type.
MaxKurtosisOfNumericAtts
480.23
Maximum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
-1
Minimum of means among attributes of the numeric type.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
Quartile3AttributeEntropy
Third quartile of entropy among attributes.
MaxMeansOfNumericAtts
0.96
Maximum of means among attributes of the numeric type.
MinMutualInformation
Minimal mutual information between the nominal attributes and the target attribute.
PercentageOfMissingValues
0
Percentage of missing values.
Quartile3KurtosisOfNumericAtts
1.03
Third quartile of kurtosis among attributes of the numeric type.
MaxMutualInformation
Maximum mutual information between the nominal attributes and the target attribute.
MinNominalAttDistinctValues
2
The minimal number of distinct values among attributes of the nominal type.
PercentageOfNumericFeatures
99.84
Percentage of numeric attributes.
Quartile3MeansOfNumericAtts
0.51
Third quartile of means among attributes of the numeric type.
MaxNominalAttDistinctValues
2
The maximum number of distinct values among attributes of the nominal type.
MinSkewnessOfNumericAtts
-6.2
Minimum skewness among attributes of the numeric type.
PercentageOfSymbolicFeatures
0.16
Percentage of nominal attributes.
Quartile3MutualInformation
Third quartile of mutual information between the nominal attributes and the target attribute.
MaxSkewnessOfNumericAtts
21.07
Maximum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
0.02
Minimum standard deviation of attributes of the numeric type.
Quartile1AttributeEntropy
First quartile of entropy among attributes.
Quartile3SkewnessOfNumericAtts
0.61
Third quartile of skewness among attributes of the numeric type.
MaxStdDevOfNumericAtts
0.86
Maximum standard deviation of attributes of the numeric type.
MinorityClassPercentage
50
Percentage of instances belonging to the least frequent class.
Quartile1KurtosisOfNumericAtts
-0.37
First quartile of kurtosis among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
0.35
Third quartile of standard deviation of attributes of the numeric type.
MeanAttributeEntropy
Average entropy of the attributes.
MinorityClassSize
300
Number of instances belonging to the least frequent class.
Quartile1MeansOfNumericAtts
-0.39
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.
MeanKurtosisOfNumericAtts
11.2
Mean kurtosis among attributes of the numeric type.
NumberOfBinaryFeatures
1
Number of binary attributes.
Quartile1MutualInformation
First quartile of mutual information between the nominal attributes and the target attribute.
MeanMeansOfNumericAtts
0.05
Mean of means among attributes of the numeric type.
Quartile1SkewnessOfNumericAtts
-0.69
First quartile of skewness among attributes of the numeric type.
AutoCorrelation
0.3
Average class difference between consecutive instances.
MeanMutualInformation
Average mutual information between the nominal attributes and the target attribute.
Quartile1StdDevOfNumericAtts
0.25
First quartile of standard deviation of attributes of the numeric type.
Show all 62 properties

12 tasks

Supervised Classification on isolet
0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
Learning Curve on isolet
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on isolet
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Supervised Data Stream Classification on isolet
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: class
Clustering on isolet
0 runs - estimation_procedure: 50 times Clustering
Clustering on isolet
0 runs - estimation_procedure: 50 times Clustering
Clustering on isolet
0 runs - estimation_procedure: 50 times Clustering
Clustering on isolet
0 runs - estimation_procedure: 50 times Clustering
Clustering on isolet
0 runs - estimation_procedure: 50 times Clustering
Clustering on isolet
0 runs - estimation_procedure: 50 times Clustering
Clustering on isolet
0 runs - estimation_procedure: 50 times Clustering
Clustering on isolet
0 runs - estimation_procedure: 50 times Clustering
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