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Kuzushiji-MNIST

Kuzushiji-MNIST

active ARFF CC BY-SA 4.0 Visibility: public Uploaded 23-07-2019 by Shelby Padilla
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Much of machine learning research focuses on producing models which perform well on benchmark tasks, in turn improving our understanding of the challenges associated with those tasks. From the perspective of ML researchers, the content of the task itself is largely irrelevant, and thus there have increasingly been calls for benchmark tasks to more heavily focus on problems which are of social or cultural relevance. In this work, we introduce Kuzushiji-MNIST, a dataset which focuses on Kuzushiji (cursive Japanese), as well as two larger, more challenging datasets, Kuzushiji-49 and Kuzushiji-Kanji. Through these datasets, we wish to engage themachine learning community into the world of classical Japanese literature.

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Show first 100 features

62 properties

NumberOfInstances
70000
Number of instances (rows) of the dataset.
NumberOfFeatures
785
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
784
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
99.87
Percentage of numeric attributes.
PercentageOfSymbolicFeatures
0.13
Percentage of nominal attributes.
Quartile1AttributeEntropy
First quartile of entropy among attributes.
Quartile1KurtosisOfNumericAtts
-0.92
First quartile of kurtosis among attributes of the numeric type.
Quartile1MeansOfNumericAtts
23.17
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
0.91
First quartile of skewness among attributes of the numeric type.
Quartile1StdDevOfNumericAtts
64.02
First quartile of standard deviation of attributes of the numeric type.
Quartile2AttributeEntropy
Second quartile (Median) of entropy among attributes.
Quartile2KurtosisOfNumericAtts
0.37
Second quartile (Median) of kurtosis among attributes of the numeric type.
Quartile2MeansOfNumericAtts
51.56
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
1.44
Second quartile (Median) of skewness among attributes of the numeric type.
Quartile2StdDevOfNumericAtts
90.4
Second quartile (Median) of standard deviation of attributes of the numeric type.
Quartile3AttributeEntropy
Third quartile of entropy among attributes.
Quartile3KurtosisOfNumericAtts
6.34
Third quartile of kurtosis among attributes of the numeric type.
Quartile3MeansOfNumericAtts
72.74
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
2.77
Third quartile of skewness among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
100.79
Third quartile of standard deviation of attributes of the numeric type.
AutoCorrelation
0.1
Average class difference between consecutive instances.
MeanMeansOfNumericAtts
48.64
Mean of means among attributes of the numeric type.
ClassEntropy
3.32
Entropy of the target attribute values.
Dimensionality
0.01
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
10
Percentage of instances belonging to the most frequent class.
MajorityClassSize
7000
Number of instances belonging to the most frequent class.
MaxAttributeEntropy
Maximum entropy among attributes.
MaxKurtosisOfNumericAtts
1455.17
Maximum kurtosis among attributes of the numeric type.
MaxMeansOfNumericAtts
96.9
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
35.55
Maximum skewness among attributes of the numeric type.
MaxStdDevOfNumericAtts
107.45
Maximum standard deviation of attributes of the numeric type.
MeanAttributeEntropy
Average entropy of the attributes.
MeanKurtosisOfNumericAtts
15.75
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
2.48
Mean skewness among attributes of the numeric type.
MeanStdDevOfNumericAtts
79.73
Mean standard deviation of attributes of the numeric type.
MinAttributeEntropy
Minimal entropy among attributes.
MinKurtosisOfNumericAtts
-1.54
Minimum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
0.19
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
0.46
Minimum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
4.94
Minimum standard deviation of attributes of the numeric type.
MinorityClassPercentage
10
Percentage of instances belonging to the least frequent class.
MinorityClassSize
7000
Number of instances belonging to the least frequent class.
Show all 62 properties

13 tasks

Supervised Classification on Kuzushiji-MNIST
0 runs - estimation_procedure: 33% Holdout set - target_feature: class
Supervised Classification on Kuzushiji-MNIST
0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
Learning Curve on Kuzushiji-MNIST
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on Kuzushiji-MNIST
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Supervised Data Stream Classification on Kuzushiji-MNIST
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: class
Clustering on Kuzushiji-MNIST
0 runs - estimation_procedure: 50 times Clustering
Clustering on Kuzushiji-MNIST
0 runs - estimation_procedure: 50 times Clustering
Clustering on Kuzushiji-MNIST
0 runs - estimation_procedure: 50 times Clustering
Clustering on Kuzushiji-MNIST
0 runs - estimation_procedure: 50 times Clustering
Clustering on Kuzushiji-MNIST
0 runs - estimation_procedure: 50 times Clustering
Clustering on Kuzushiji-MNIST
0 runs - estimation_procedure: 50 times Clustering
Clustering on Kuzushiji-MNIST
0 runs - estimation_procedure: 50 times Clustering
Clustering on Kuzushiji-MNIST
0 runs - estimation_procedure: 50 times Clustering
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