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Kuzushiji-MNIST

active ARFF CC BY-SA 4.0 Visibility: public Uploaded 23-07-2019 by Matthias Feurer
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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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pixel-0696	numeric	256 unique values 0 missing
pixel-0185	numeric	256 unique values 0 missing
pixel-0441	numeric	256 unique values 0 missing
pixel-0697	numeric	255 unique values 0 missing
pixel-0186	numeric	256 unique values 0 missing
pixel-0442	numeric	256 unique values 0 missing
pixel-0698	numeric	256 unique values 0 missing
pixel-0187	numeric	256 unique values 0 missing
pixel-0443	numeric	256 unique values 0 missing
pixel-0699	numeric	252 unique values 0 missing
pixel-0188	numeric	256 unique values 0 missing
pixel-0444	numeric	256 unique values 0 missing
pixel-0700	numeric	244 unique values 0 missing
pixel-0189	numeric	256 unique values 0 missing
pixel-0445	numeric	256 unique values 0 missing
pixel-0701	numeric	256 unique values 0 missing
pixel-0190	numeric	256 unique values 0 missing
pixel-0446	numeric	256 unique values 0 missing
pixel-0702	numeric	256 unique values 0 missing
pixel-0191	numeric	256 unique values 0 missing
pixel-0447	numeric	256 unique values 0 missing
pixel-0703	numeric	256 unique values 0 missing
pixel-0192	numeric	256 unique values 0 missing
pixel-0448	numeric	255 unique values 0 missing
pixel-0704	numeric	256 unique values 0 missing
pixel-0193	numeric	256 unique values 0 missing
pixel-0449	numeric	256 unique values 0 missing
pixel-0705	numeric	256 unique values 0 missing
pixel-0194	numeric	256 unique values 0 missing
pixel-0450	numeric	256 unique values 0 missing
pixel-0706	numeric	256 unique values 0 missing
pixel-0195	numeric	256 unique values 0 missing
pixel-0451	numeric	256 unique values 0 missing
pixel-0707	numeric	256 unique values 0 missing
pixel-0196	numeric	255 unique values 0 missing
pixel-0452	numeric	256 unique values 0 missing
pixel-0708	numeric	256 unique values 0 missing
pixel-0197	numeric	256 unique values 0 missing
pixel-0453	numeric	256 unique values 0 missing
pixel-0709	numeric	256 unique values 0 missing
pixel-0198	numeric	256 unique values 0 missing
pixel-0454	numeric	256 unique values 0 missing
pixel-0710	numeric	256 unique values 0 missing
pixel-0199	numeric	256 unique values 0 missing
pixel-0455	numeric	256 unique values 0 missing
pixel-0711	numeric	256 unique values 0 missing
pixel-0200	numeric	256 unique values 0 missing
pixel-0456	numeric	256 unique values 0 missing
pixel-0712	numeric	256 unique values 0 missing
pixel-0201	numeric	256 unique values 0 missing
pixel-0457	numeric	256 unique values 0 missing
pixel-0713	numeric	256 unique values 0 missing
pixel-0202	numeric	256 unique values 0 missing
pixel-0458	numeric	256 unique values 0 missing
pixel-0714	numeric	256 unique values 0 missing
pixel-0203	numeric	256 unique values 0 missing
pixel-0459	numeric	256 unique values 0 missing
pixel-0715	numeric	256 unique values 0 missing
pixel-0204	numeric	256 unique values 0 missing
pixel-0460	numeric	256 unique values 0 missing
pixel-0716	numeric	256 unique values 0 missing
pixel-0205	numeric	256 unique values 0 missing
pixel-0461	numeric	256 unique values 0 missing
pixel-0717	numeric	256 unique values 0 missing
pixel-0206	numeric	256 unique values 0 missing
pixel-0462	numeric	256 unique values 0 missing
pixel-0718	numeric	256 unique values 0 missing
pixel-0207	numeric	256 unique values 0 missing
pixel-0463	numeric	256 unique values 0 missing
pixel-0719	numeric	256 unique values 0 missing
pixel-0208	numeric	256 unique values 0 missing
pixel-0464	numeric	256 unique values 0 missing
pixel-0720	numeric	256 unique values 0 missing
pixel-0209	numeric	256 unique values 0 missing
pixel-0465	numeric	256 unique values 0 missing
pixel-0721	numeric	256 unique values 0 missing
pixel-0210	numeric	256 unique values 0 missing
pixel-0466	numeric	256 unique values 0 missing
pixel-0722	numeric	256 unique values 0 missing
pixel-0211	numeric	256 unique values 0 missing
pixel-0467	numeric	256 unique values 0 missing
pixel-0723	numeric	256 unique values 0 missing
pixel-0212	numeric	256 unique values 0 missing
pixel-0468	numeric	256 unique values 0 missing
pixel-0724	numeric	256 unique values 0 missing
pixel-0213	numeric	256 unique values 0 missing
pixel-0469	numeric	256 unique values 0 missing
pixel-0725	numeric	256 unique values 0 missing
pixel-0214	numeric	256 unique values 0 missing
pixel-0470	numeric	256 unique values 0 missing
pixel-0726	numeric	256 unique values 0 missing
pixel-0215	numeric	256 unique values 0 missing
pixel-0471	numeric	256 unique values 0 missing
pixel-0727	numeric	251 unique values 0 missing
pixel-0216	numeric	256 unique values 0 missing
pixel-0472	numeric	256 unique values 0 missing
pixel-0728	numeric	230 unique values 0 missing
pixel-0217	numeric	256 unique values 0 missing
pixel-0473	numeric	256 unique values 0 missing
pixel-0729	numeric	256 unique values 0 missing
pixel-0218	numeric	256 unique values 0 missing
pixel-0474	numeric	256 unique values 0 missing
pixel-0730	numeric	256 unique values 0 missing
pixel-0219	numeric	256 unique values 0 missing
pixel-0475	numeric	256 unique values 0 missing
pixel-0731	numeric	256 unique values 0 missing
pixel-0220	numeric	256 unique values 0 missing
pixel-0476	numeric	255 unique values 0 missing
pixel-0732	numeric	256 unique values 0 missing
pixel-0221	numeric	256 unique values 0 missing
pixel-0477	numeric	256 unique values 0 missing
pixel-0733	numeric	256 unique values 0 missing
pixel-0222	numeric	256 unique values 0 missing
pixel-0478	numeric	256 unique values 0 missing
pixel-0734	numeric	256 unique values 0 missing
pixel-0223	numeric	256 unique values 0 missing
pixel-0479	numeric	256 unique values 0 missing
pixel-0735	numeric	256 unique values 0 missing
pixel-0224	numeric	254 unique values 0 missing
pixel-0480	numeric	256 unique values 0 missing
pixel-0736	numeric	256 unique values 0 missing
pixel-0225	numeric	256 unique values 0 missing
pixel-0481	numeric	256 unique values 0 missing
pixel-0737	numeric	256 unique values 0 missing
pixel-0226	numeric	256 unique values 0 missing
pixel-0482	numeric	256 unique values 0 missing
pixel-0738	numeric	256 unique values 0 missing
pixel-0227	numeric	256 unique values 0 missing
pixel-0483	numeric	256 unique values 0 missing
pixel-0739	numeric	256 unique values 0 missing
pixel-0228	numeric	256 unique values 0 missing
pixel-0484	numeric	256 unique values 0 missing
pixel-0740	numeric	256 unique values 0 missing
pixel-0229	numeric	256 unique values 0 missing
pixel-0485	numeric	256 unique values 0 missing
pixel-0741	numeric	256 unique values 0 missing
pixel-0230	numeric	256 unique values 0 missing
pixel-0486	numeric	256 unique values 0 missing
pixel-0742	numeric	256 unique values 0 missing
pixel-0231	numeric	256 unique values 0 missing
pixel-0487	numeric	256 unique values 0 missing
pixel-0743	numeric	256 unique values 0 missing
pixel-0232	numeric	256 unique values 0 missing
pixel-0488	numeric	256 unique values 0 missing
pixel-0744	numeric	256 unique values 0 missing
pixel-0233	numeric	256 unique values 0 missing
pixel-0489	numeric	256 unique values 0 missing
pixel-0745	numeric	256 unique values 0 missing
pixel-0234	numeric	256 unique values 0 missing
pixel-0490	numeric	256 unique values 0 missing
pixel-0746	numeric	256 unique values 0 missing
pixel-0235	numeric	256 unique values 0 missing
pixel-0491	numeric	256 unique values 0 missing
pixel-0747	numeric	256 unique values 0 missing
pixel-0236	numeric	256 unique values 0 missing
pixel-0492	numeric	256 unique values 0 missing
pixel-0748	numeric	256 unique values 0 missing
pixel-0237	numeric	256 unique values 0 missing
pixel-0493	numeric	256 unique values 0 missing
pixel-0749	numeric	256 unique values 0 missing
pixel-0238	numeric	256 unique values 0 missing
pixel-0494	numeric	256 unique values 0 missing
pixel-0750	numeric	256 unique values 0 missing
pixel-0239	numeric	256 unique values 0 missing
pixel-0495	numeric	256 unique values 0 missing
pixel-0751	numeric	256 unique values 0 missing
pixel-0240	numeric	256 unique values 0 missing
pixel-0496	numeric	256 unique values 0 missing
pixel-0752	numeric	256 unique values 0 missing
pixel-0241	numeric	256 unique values 0 missing
pixel-0497	numeric	256 unique values 0 missing
pixel-0753	numeric	256 unique values 0 missing
pixel-0242	numeric	256 unique values 0 missing
pixel-0498	numeric	256 unique values 0 missing
pixel-0754	numeric	253 unique values 0 missing
pixel-0243	numeric	256 unique values 0 missing
pixel-0499	numeric	256 unique values 0 missing
pixel-0755	numeric	242 unique values 0 missing
pixel-0244	numeric	256 unique values 0 missing
pixel-0500	numeric	256 unique values 0 missing
pixel-0756	numeric	171 unique values 0 missing
pixel-0245	numeric	256 unique values 0 missing
pixel-0501	numeric	256 unique values 0 missing
pixel-0757	numeric	253 unique values 0 missing
pixel-0246	numeric	256 unique values 0 missing
pixel-0502	numeric	256 unique values 0 missing
pixel-0758	numeric	256 unique values 0 missing
pixel-0247	numeric	256 unique values 0 missing
pixel-0503	numeric	256 unique values 0 missing
pixel-0759	numeric	256 unique values 0 missing
pixel-0248	numeric	256 unique values 0 missing
pixel-0504	numeric	256 unique values 0 missing
pixel-0760	numeric	256 unique values 0 missing
pixel-0249	numeric	256 unique values 0 missing
pixel-0505	numeric	256 unique values 0 missing
pixel-0761	numeric	256 unique values 0 missing
pixel-0250	numeric	256 unique values 0 missing
pixel-0506	numeric	256 unique values 0 missing
pixel-0762	numeric	256 unique values 0 missing
pixel-0251	numeric	256 unique values 0 missing
pixel-0507	numeric	256 unique values 0 missing
pixel-0763	numeric	256 unique values 0 missing
pixel-0252	numeric	256 unique values 0 missing
pixel-0508	numeric	256 unique values 0 missing
pixel-0764	numeric	256 unique values 0 missing
pixel-0253	numeric	256 unique values 0 missing
pixel-0509	numeric	256 unique values 0 missing
pixel-0765	numeric	256 unique values 0 missing
pixel-0254	numeric	256 unique values 0 missing
pixel-0510	numeric	256 unique values 0 missing
pixel-0766	numeric	256 unique values 0 missing
pixel-0255	numeric	256 unique values 0 missing
pixel-0511	numeric	256 unique values 0 missing
pixel-0767	numeric	256 unique values 0 missing

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

Number of distinct values of the target attribute (if it is nominal).

NumberOfMissingValues

Number of missing values in the dataset.

NumberOfInstancesWithMissingValues

Number of instances with at least one value missing.

NumberOfNumericFeatures

784

Number of numeric attributes.

NumberOfSymbolicFeatures

Number of nominal attributes.

EquivalentNumberOfAtts

Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.

MeanSkewnessOfNumericAtts

2.48

Mean skewness among attributes of the numeric type.

Quartile2MeansOfNumericAtts

51.56

Second quartile (Median) of means among attributes of the numeric type.

MajorityClassPercentage

Percentage of instances belonging to the most frequent class.

MeanStdDevOfNumericAtts

79.73

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

7000

Number of instances belonging to the most frequent class.

MinAttributeEntropy

Minimal entropy among attributes.

Quartile2SkewnessOfNumericAtts

1.44

Second quartile (Median) of skewness among attributes of the numeric type.

MaxAttributeEntropy

Maximum entropy among attributes.

MinKurtosisOfNumericAtts

-1.54

Minimum kurtosis among attributes of the numeric type.

PercentageOfBinaryFeatures

Percentage of binary attributes.

Quartile2StdDevOfNumericAtts

90.4

Second quartile (Median) of standard deviation of attributes of the numeric type.

MaxKurtosisOfNumericAtts

1455.17

Maximum kurtosis among attributes of the numeric type.

MinMeansOfNumericAtts

0.19

Minimum of means among attributes of the numeric type.

PercentageOfInstancesWithMissingValues

Percentage of instances having missing values.

Quartile3AttributeEntropy

Third quartile of entropy among attributes.

MaxMeansOfNumericAtts

96.9

Maximum of means among attributes of the numeric type.

MinMutualInformation

Minimal mutual information between the nominal attributes and the target attribute.

PercentageOfMissingValues

Percentage of missing values.

Quartile3KurtosisOfNumericAtts

6.34

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

99.87

Percentage of numeric attributes.

Quartile3MeansOfNumericAtts

72.74

Third quartile of means among attributes of the numeric type.

MaxNominalAttDistinctValues

The maximum number of distinct values among attributes of the nominal type.

MinSkewnessOfNumericAtts

0.46

Minimum skewness among attributes of the numeric type.

PercentageOfSymbolicFeatures

0.13

Percentage of nominal attributes.

Quartile3MutualInformation

Third quartile of mutual information between the nominal attributes and the target attribute.

MaxSkewnessOfNumericAtts

35.55

Maximum skewness among attributes of the numeric type.

MinStdDevOfNumericAtts

4.94

Minimum standard deviation of attributes of the numeric type.

Quartile1AttributeEntropy

First quartile of entropy among attributes.

Quartile3SkewnessOfNumericAtts

2.77

Third quartile of skewness among attributes of the numeric type.

MaxStdDevOfNumericAtts

107.45

Maximum standard deviation of attributes of the numeric type.

MinorityClassPercentage

Percentage of instances belonging to the least frequent class.

Quartile1KurtosisOfNumericAtts

-0.92

First quartile of kurtosis among attributes of the numeric type.

Quartile3StdDevOfNumericAtts

100.79

Third quartile of standard deviation of attributes of the numeric type.

MeanAttributeEntropy

Average entropy of the attributes.

MinorityClassSize

7000

Number of instances belonging to the least frequent class.

Quartile1MeansOfNumericAtts

23.17

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.

MeanKurtosisOfNumericAtts

15.75

Mean kurtosis among attributes of the numeric type.

NumberOfBinaryFeatures

Number of binary attributes.

Quartile1MutualInformation

First quartile of mutual information between the nominal attributes and the target attribute.

MeanMeansOfNumericAtts

48.64

Mean of means among attributes of the numeric type.

Quartile1SkewnessOfNumericAtts

0.91

First quartile of skewness among attributes of the numeric type.

AutoCorrelation

0.1

Average class difference between consecutive instances.

MeanMutualInformation

Average mutual information between the nominal attributes and the target attribute.

Quartile1StdDevOfNumericAtts

64.02

First quartile of standard deviation of attributes of the numeric type.

ClassEntropy

3.32

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

0.01

Number of attributes divided by the number of instances.

MeanNominalAttDistinctValues

Average number of distinct values among the attributes of the nominal type.

Quartile2KurtosisOfNumericAtts

0.37

Second quartile (Median) of kurtosis among attributes of the numeric type.

Show all 62 properties