Data
mnist_rotation

mnist_rotation

active ARFF Public Domain (CC0) Visibility: public Uploaded 22-03-2018 by Silvia Nunes
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rotated MNIS digits, from http://www.iro.umontreal.ca/~lisa/twiki/bin/view.cgi/Public/MnistVariations

785 features

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Show first 100 features

62 properties

NumberOfInstances
62000
Number of instances (rows) of the dataset.
NumberOfFeatures
785
Number of attributes (columns) of the dataset.
NumberOfClasses
0
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
785
Number of numeric attributes.
NumberOfSymbolicFeatures
0
Number of nominal attributes.
MeanKurtosisOfNumericAtts
-0.98
Mean kurtosis among attributes of the numeric type.
NumberOfBinaryFeatures
0
Number of binary attributes.
Quartile1MutualInformation
First quartile of mutual information between the nominal attributes and the target attribute.
MeanMeansOfNumericAtts
0.55
Mean of means among attributes of the numeric type.
Quartile1SkewnessOfNumericAtts
-0.17
First quartile of skewness among attributes of the numeric type.
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.
AutoCorrelation
-2.31
Average class difference between consecutive instances.
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.
ClassEntropy
Entropy of the target attribute values.
MeanNominalAttDistinctValues
Average number of distinct values among the attributes of the nominal type.
Quartile2KurtosisOfNumericAtts
-1.02
Second quartile (Median) of kurtosis among attributes of the numeric type.
Dimensionality
0.01
Number of attributes divided by the number of instances.
MeanSkewnessOfNumericAtts
-0
Mean skewness among attributes of the numeric type.
Quartile2MeansOfNumericAtts
0.51
Second quartile (Median) of means 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.
MeanStdDevOfNumericAtts
0.27
Mean standard deviation of attributes of the numeric type.
Quartile2MutualInformation
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
MajorityClassPercentage
Percentage of instances belonging to the most frequent class.
MinAttributeEntropy
Minimal entropy among attributes.
Quartile2SkewnessOfNumericAtts
0.1
Second quartile (Median) of skewness among attributes of the numeric type.
MajorityClassSize
Number of instances belonging to the most frequent class.
MaxAttributeEntropy
Maximum entropy among attributes.
MinKurtosisOfNumericAtts
-1.25
Minimum kurtosis among attributes of the numeric type.
PercentageOfBinaryFeatures
0
Percentage of binary attributes.
Quartile2StdDevOfNumericAtts
0.26
Second quartile (Median) of standard deviation of attributes of the numeric type.
MaxKurtosisOfNumericAtts
-0.72
Maximum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
0.47
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
4.44
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
-0.88
Third quartile of kurtosis among attributes of the numeric type.
MaxMutualInformation
Maximum mutual information between the nominal attributes and the target attribute.
MinNominalAttDistinctValues
The minimal number of distinct values among attributes of the nominal type.
PercentageOfNumericFeatures
100
Percentage of numeric attributes.
Quartile3MeansOfNumericAtts
0.6
Third quartile of means among attributes of the numeric type.
MaxNominalAttDistinctValues
The maximum number of distinct values among attributes of the nominal type.
MinSkewnessOfNumericAtts
-0.49
Minimum skewness among attributes of the numeric type.
PercentageOfSymbolicFeatures
0
Percentage of nominal attributes.
Quartile3MutualInformation
Third quartile of mutual information between the nominal attributes and the target attribute.
MaxSkewnessOfNumericAtts
0.22
Maximum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
0.24
Minimum standard deviation of attributes of the numeric type.
Quartile1AttributeEntropy
First quartile of entropy among attributes.
Quartile3SkewnessOfNumericAtts
0.15
Third quartile of skewness among attributes of the numeric type.
MaxStdDevOfNumericAtts
2.89
Maximum standard deviation of attributes of the numeric type.
MinorityClassPercentage
Percentage of instances belonging to the least frequent class.
Quartile1KurtosisOfNumericAtts
-1.08
First quartile of kurtosis among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
0.28
Third quartile of standard deviation of attributes of the numeric type.
MeanAttributeEntropy
Average entropy of the attributes.
MinorityClassSize
Number of instances belonging to the least frequent class.
Quartile1MeansOfNumericAtts
0.49
First quartile of means among attributes of the numeric type.
StdvNominalAttDistinctValues
Standard deviation of the number of distinct values among attributes of the nominal type.
Show all 62 properties

13 tasks

Supervised Regression on mnist_rotation
0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
Supervised Regression on mnist_rotation
0 runs - estimation_procedure: Custom 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
Supervised Regression on mnist_rotation
0 runs - estimation_procedure: Test on Training Data - evaluation_measure: predictive_accuracy - target_feature: class
Supervised Regression on mnist_rotation
0 runs - estimation_procedure: 5 times 2-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
Clustering on mnist_rotation
0 runs - estimation_procedure: 50 times Clustering
Clustering on mnist_rotation
0 runs - estimation_procedure: 50 times Clustering
Clustering on mnist_rotation
0 runs - estimation_procedure: 50 times Clustering
Clustering on mnist_rotation
0 runs - estimation_procedure: 50 times Clustering
Clustering on mnist_rotation
0 runs - estimation_procedure: 50 times Clustering
Clustering on mnist_rotation
0 runs - estimation_procedure: 50 times Clustering
Clustering on mnist_rotation
0 runs - estimation_procedure: 50 times Clustering
Clustering on mnist_rotation
0 runs - estimation_procedure: 50 times Clustering
Clustering on mnist_rotation
0 runs - estimation_procedure: 50 times Clustering
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