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USPS

USPS

active ARFF Public Domain (CC0) Visibility: public Uploaded 14-05-2018 by Irfan Nur Afif
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The dataset and this description is made available on http://www-stat.stanford.edu/~tibs/ElemStatLearn/data.html. Normalized handwritten digits, automatically scanned from envelopes by the U.S. Postal Service. The original scanned digits are binary and of different sizes and orientations; the images here have been deslanted and size normalized, resulting in 16 x 16 grayscale images (Le Cun et al., 1990). The data are in two gzipped files, and each line consists of the digit id (0-9) followed by the 256 grayscale values. There are 7291 training observations and 2007 test observations, distributed as follows: 0 1 2 3 4 5 6 7 8 9 Total Train 1194 1005 731 658 652 556 664 645 542 644 7291 Test 359 264 198 166 200 160 170 147 166 177 2007 or as proportions: 0 1 2 3 4 5 6 7 8 9 Train 0.16 0.14 0.1 0.09 0.09 0.08 0.09 0.09 0.07 0.09 Test 0.18 0.13 0.1 0.08 0.10 0.08 0.08 0.07 0.08 0.09 Alternatively, the training data are available as separate files per digit (and hence without the digit identifier in each row) The test set is notoriously "difficult", and a 2.5% error rate is excellent. These data were kindly made available by the neural network group at AT&T research labs (thanks to Yann Le Cunn). PS: In this dataset, the class is represented as 1-10

257 features

int0 (target)nominal10 unique values
0 missing
double256numeric1834 unique values
0 missing
double1numeric1617 unique values
0 missing
double2numeric3010 unique values
0 missing
double3numeric4733 unique values
0 missing
double4numeric6345 unique values
0 missing
double5numeric8037 unique values
0 missing
double6numeric8948 unique values
0 missing
double7numeric9092 unique values
0 missing
double8numeric9136 unique values
0 missing
double9numeric9123 unique values
0 missing
double10numeric9122 unique values
0 missing
double11numeric9033 unique values
0 missing
double12numeric8260 unique values
0 missing
double13numeric6775 unique values
0 missing
double14numeric5243 unique values
0 missing
double15numeric3403 unique values
0 missing
double16numeric1931 unique values
0 missing
double17numeric2326 unique values
0 missing
double18numeric4144 unique values
0 missing
double19numeric5974 unique values
0 missing
double20numeric7236 unique values
0 missing
double21numeric8771 unique values
0 missing
double22numeric9198 unique values
0 missing
double23numeric9226 unique values
0 missing
double24numeric9219 unique values
0 missing
double25numeric9206 unique values
0 missing
double26numeric9206 unique values
0 missing
double27numeric9188 unique values
0 missing
double28numeric8795 unique values
0 missing
double29numeric7404 unique values
0 missing
double30numeric6143 unique values
0 missing
double31numeric4371 unique values
0 missing
double32numeric2528 unique values
0 missing
double33numeric3014 unique values
0 missing
double34numeric5064 unique values
0 missing
double35numeric6671 unique values
0 missing
double36numeric7797 unique values
0 missing
double37numeric9050 unique values
0 missing
double38numeric9259 unique values
0 missing
double39numeric9265 unique values
0 missing
double40numeric9260 unique values
0 missing
double41numeric9245 unique values
0 missing
double42numeric9247 unique values
0 missing
double43numeric9212 unique values
0 missing
double44numeric8954 unique values
0 missing
double45numeric7643 unique values
0 missing
double46numeric6617 unique values
0 missing
double47numeric5024 unique values
0 missing
double48numeric3091 unique values
0 missing
double49numeric3497 unique values
0 missing
double50numeric5578 unique values
0 missing
double51numeric7116 unique values
0 missing
double52numeric8108 unique values
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double53numeric9122 unique values
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double54numeric9266 unique values
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double55numeric9270 unique values
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double56numeric9257 unique values
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double57numeric9269 unique values
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double58numeric9261 unique values
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double59numeric9232 unique values
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double60numeric8944 unique values
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double61numeric7679 unique values
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double62numeric6758 unique values
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double63numeric5374 unique values
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double64numeric3422 unique values
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double65numeric3711 unique values
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double66numeric5672 unique values
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double67numeric7239 unique values
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double68numeric8140 unique values
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double69numeric9085 unique values
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double70numeric9254 unique values
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double71numeric9272 unique values
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double72numeric9257 unique values
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double73numeric9254 unique values
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double74numeric9259 unique values
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double75numeric9224 unique values
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double76numeric8831 unique values
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double77numeric7651 unique values
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double78numeric6791 unique values
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double79numeric5452 unique values
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double80numeric3535 unique values
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double81numeric3729 unique values
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double82numeric5580 unique values
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double83numeric7058 unique values
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double84numeric7891 unique values
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double85numeric8854 unique values
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double86numeric9149 unique values
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double88numeric9182 unique values
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double89numeric9217 unique values
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double90numeric9247 unique values
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double91numeric9202 unique values
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double92numeric8784 unique values
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double93numeric7672 unique values
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double94numeric6814 unique values
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double95numeric5430 unique values
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double96numeric3572 unique values
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double97numeric3743 unique values
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double98numeric5482 unique values
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double99numeric6848 unique values
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double100numeric7644 unique values
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double101numeric8614 unique values
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double102numeric8912 unique values
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double103numeric8997 unique values
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double104numeric9075 unique values
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double105numeric9129 unique values
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double106numeric9212 unique values
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double107numeric9203 unique values
0 missing
double108numeric8899 unique values
0 missing
double109numeric7845 unique values
0 missing
double110numeric6906 unique values
0 missing
double111numeric5434 unique values
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double112numeric3647 unique values
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double113numeric3828 unique values
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double114numeric5400 unique values
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double115numeric6646 unique values
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double116numeric7518 unique values
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double117numeric8507 unique values
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double118numeric8840 unique values
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double119numeric8974 unique values
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double120numeric8982 unique values
0 missing
double121numeric8944 unique values
0 missing
double122numeric9093 unique values
0 missing
double123numeric9210 unique values
0 missing
double124numeric9026 unique values
0 missing
double125numeric8028 unique values
0 missing
double126numeric7034 unique values
0 missing
double127numeric5508 unique values
0 missing
double128numeric3770 unique values
0 missing
double129numeric3954 unique values
0 missing
double130numeric5348 unique values
0 missing
double131numeric6500 unique values
0 missing
double132numeric7384 unique values
0 missing
double133numeric8383 unique values
0 missing
double134numeric8806 unique values
0 missing
double135numeric8991 unique values
0 missing
double136numeric8854 unique values
0 missing
double137numeric8779 unique values
0 missing
double138numeric9059 unique values
0 missing
double139numeric9236 unique values
0 missing
double140numeric9076 unique values
0 missing
double141numeric8081 unique values
0 missing
double142numeric7053 unique values
0 missing
double143numeric5562 unique values
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double144numeric3939 unique values
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double145numeric4124 unique values
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double146numeric5381 unique values
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double147numeric6356 unique values
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double148numeric7171 unique values
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double149numeric8242 unique values
0 missing
double150numeric8853 unique values
0 missing
double151numeric8986 unique values
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double152numeric8813 unique values
0 missing
double153numeric8834 unique values
0 missing
double154numeric9123 unique values
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double155numeric9225 unique values
0 missing
double156numeric9080 unique values
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double157numeric8067 unique values
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double158numeric6953 unique values
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double159numeric5574 unique values
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double160numeric4149 unique values
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double161numeric4292 unique values
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double162numeric5444 unique values
0 missing
double163numeric6247 unique values
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double164numeric6957 unique values
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double165numeric8156 unique values
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double166numeric8934 unique values
0 missing
double167numeric9056 unique values
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double168numeric8934 unique values
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double169numeric9043 unique values
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double170numeric9222 unique values
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double171numeric9264 unique values
0 missing
double172numeric9063 unique values
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double173numeric7982 unique values
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double174numeric6771 unique values
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double175numeric5523 unique values
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double176numeric4269 unique values
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double177numeric4299 unique values
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double178numeric5422 unique values
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double179numeric6155 unique values
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double180numeric6907 unique values
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double181numeric8333 unique values
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double182numeric9127 unique values
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double183numeric9231 unique values
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double184numeric9220 unique values
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double185numeric9247 unique values
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double186numeric9267 unique values
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double187numeric9259 unique values
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double188numeric9068 unique values
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double189numeric7769 unique values
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double190numeric6484 unique values
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double191numeric5405 unique values
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double192numeric4228 unique values
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double193numeric4219 unique values
0 missing
double194numeric5314 unique values
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double195numeric6018 unique values
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double196numeric6789 unique values
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double197numeric8395 unique values
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double198numeric9156 unique values
0 missing
double199numeric9262 unique values
0 missing
double200numeric9274 unique values
0 missing
double201numeric9267 unique values
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double202numeric9278 unique values
0 missing
double203numeric9271 unique values
0 missing
double204numeric9000 unique values
0 missing
double205numeric7363 unique values
0 missing
double206numeric6140 unique values
0 missing
double207numeric5185 unique values
0 missing
double208numeric4015 unique values
0 missing
double209numeric3957 unique values
0 missing
double210numeric5129 unique values
0 missing
double211numeric5854 unique values
0 missing
double212numeric6667 unique values
0 missing
double213numeric8371 unique values
0 missing
double214numeric9123 unique values
0 missing
double215numeric9248 unique values
0 missing
double216numeric9254 unique values
0 missing
double217numeric9265 unique values
0 missing
double218numeric9270 unique values
0 missing
double219numeric9243 unique values
0 missing
double220numeric8825 unique values
0 missing
double221numeric6969 unique values
0 missing
double222numeric5836 unique values
0 missing
double223numeric4843 unique values
0 missing
double224numeric3554 unique values
0 missing
double225numeric3314 unique values
0 missing
double226numeric4718 unique values
0 missing
double227numeric5628 unique values
0 missing
double228numeric6485 unique values
0 missing
double229numeric8203 unique values
0 missing
double230numeric9005 unique values
0 missing
double231numeric9194 unique values
0 missing
double232numeric9221 unique values
0 missing
double233numeric9224 unique values
0 missing
double234numeric9218 unique values
0 missing
double235numeric9150 unique values
0 missing
double236numeric8459 unique values
0 missing
double237numeric6566 unique values
0 missing
double238numeric5446 unique values
0 missing
double239numeric4205 unique values
0 missing
double240numeric2791 unique values
0 missing
double241numeric2288 unique values
0 missing
double242numeric3799 unique values
0 missing
double243numeric5140 unique values
0 missing
double244numeric6107 unique values
0 missing
double245numeric7825 unique values
0 missing
double246numeric8841 unique values
0 missing
double247numeric9076 unique values
0 missing
double248numeric9139 unique values
0 missing
double249numeric9142 unique values
0 missing
double250numeric9107 unique values
0 missing
double251numeric8923 unique values
0 missing
double252numeric7824 unique values
0 missing
double253numeric5988 unique values
0 missing
double254numeric4571 unique values
0 missing
double255numeric3120 unique values
0 missing

62 properties

9298
Number of instances (rows) of the dataset.
257
Number of attributes (columns) of the dataset.
10
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
256
Number of numeric attributes.
1
Number of nominal attributes.
0
Percentage of binary attributes.
0.56
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
-1.57
Minimum kurtosis among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
105.45
Maximum kurtosis among attributes of the numeric type.
-0.99
Minimum of means among attributes of the numeric type.
0
Percentage of missing values.
3.94
Third quartile of kurtosis among attributes of the numeric type.
0.24
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
99.61
Percentage of numeric attributes.
-0.25
Third quartile of means among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
10
The minimal number of distinct values among attributes of the nominal type.
0.39
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
10
The maximum number of distinct values among attributes of the nominal type.
-0.95
Minimum skewness among attributes of the numeric type.
First quartile of entropy among attributes.
2.2
Third quartile of skewness among attributes of the numeric type.
9.39
Maximum skewness among attributes of the numeric type.
0.05
Minimum standard deviation of attributes of the numeric type.
-1.23
First quartile of kurtosis among attributes of the numeric type.
0.62
Third quartile of standard deviation of attributes of the numeric type.
0.68
Maximum standard deviation of attributes of the numeric type.
7.61
Percentage of instances belonging to the least frequent class.
-0.8
First quartile of means among attributes of the numeric type.
0
Standard deviation of the number of distinct values among attributes of the nominal type.
Average entropy of the attributes.
708
Number of instances belonging to the least frequent class.
First quartile of mutual information between the nominal attributes and the target attribute.
4.77
Mean kurtosis among attributes of the numeric type.
0
Number of binary attributes.
0.28
First quartile of skewness among attributes of the numeric type.
-0.5
Mean of means among attributes of the numeric type.
0.39
First quartile of standard deviation of attributes of the numeric type.
0.12
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
Second quartile (Median) of entropy among attributes.
3.27
Entropy of the target attribute values.
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
-0.69
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.03
Number of attributes divided by the number of instances.
10
Average number of distinct values among the attributes of the nominal type.
-0.47
Second quartile (Median) of means among attributes of the numeric type.
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
1.47
Mean skewness among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
16.7
Percentage of instances belonging to the most frequent class.
0.49
Mean standard deviation of attributes of the numeric type.
0.81
Second quartile (Median) of skewness among attributes of the numeric type.
1553
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.

1 tasks

56 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: int0
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