Data
Semeion-train

Semeion-train

in_preparation ARFF Publicly available Visibility: public Uploaded 20-06-2017 by Stefan Coors
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Source: The dataset was created by Tactile Srl, Brescia, Italy (http://www.tattile.it) and donated in 1994 to Semeion Research Center of Sciences of Communication, Rome, Italy (http://www.semeion.it), for machine learning research. For any questions, e-mail Massimo Buscema (m.buscema '@' semeion.it) or Stefano Terzi (s.terzi '@' semeion.it) Data Set Information: 1593 handwritten digits from around 80 persons were scanned, stretched in a rectangular box 16x16 in a gray scale of 256 values.Then each pixel of each image was scaled into a bolean (1/0) value using a fixed threshold. Each person wrote on a paper all the digits from 0 to 9, twice. The commitment was to write the digit the first time in the normal way (trying to write each digit accurately) and the second time in a fast way (with no accuracy). The best validation protocol for this dataset seems to be a 5x2CV, 50% Tune (Train +Test) and completly blind 50% Validation Attribute Information: This dataset consists of 1593 records (rows) and 256 attributes (columns). Each record represents a handwritten digit, orginally scanned with a resolution of 256 grays scale (28). Each pixel of the each original scanned image was first stretched, and after scaled between 0 and 1 (setting to 0 every pixel whose value was under tha value 127 of the grey scale (127 included) and setting to 1 each pixel whose orinal value in the grey scale was over 127). Finally, each binary image was scaled again into a 16x16 square box (the final 256 binary attributes). #autoxgboost #autoweka

257 features

a_0numeric2 unique values
0 missing
classnominal10 unique values
0 missing
a_1numeric2 unique values
0 missing
a_2numeric2 unique values
0 missing
a_3numeric2 unique values
0 missing
a_4numeric2 unique values
0 missing
a_5numeric2 unique values
0 missing
a_6numeric2 unique values
0 missing
a_7numeric2 unique values
0 missing
a_8numeric2 unique values
0 missing
a_9numeric2 unique values
0 missing
a_10numeric2 unique values
0 missing
a_11numeric2 unique values
0 missing
a_12numeric2 unique values
0 missing
a_13numeric2 unique values
0 missing
a_14numeric2 unique values
0 missing
a_15numeric2 unique values
0 missing
a_16numeric2 unique values
0 missing
a_17numeric2 unique values
0 missing
a_18numeric2 unique values
0 missing
a_19numeric2 unique values
0 missing
a_20numeric2 unique values
0 missing
a_21numeric2 unique values
0 missing
a_22numeric2 unique values
0 missing
a_23numeric2 unique values
0 missing
a_24numeric2 unique values
0 missing
a_25numeric2 unique values
0 missing
a_26numeric2 unique values
0 missing
a_27numeric2 unique values
0 missing
a_28numeric2 unique values
0 missing
a_29numeric2 unique values
0 missing
a_30numeric2 unique values
0 missing
a_31numeric2 unique values
0 missing
a_32numeric2 unique values
0 missing
a_33numeric2 unique values
0 missing
a_34numeric2 unique values
0 missing
a_35numeric2 unique values
0 missing
a_36numeric2 unique values
0 missing
a_37numeric2 unique values
0 missing
a_38numeric2 unique values
0 missing
a_39numeric2 unique values
0 missing
a_40numeric2 unique values
0 missing
a_41numeric2 unique values
0 missing
a_42numeric2 unique values
0 missing
a_43numeric2 unique values
0 missing
a_44numeric2 unique values
0 missing
a_45numeric2 unique values
0 missing
a_46numeric2 unique values
0 missing
a_47numeric2 unique values
0 missing
a_48numeric2 unique values
0 missing
a_49numeric2 unique values
0 missing
a_50numeric2 unique values
0 missing
a_51numeric2 unique values
0 missing
a_52numeric2 unique values
0 missing
a_53numeric2 unique values
0 missing
a_54numeric2 unique values
0 missing
a_55numeric2 unique values
0 missing
a_56numeric2 unique values
0 missing
a_57numeric2 unique values
0 missing
a_58numeric2 unique values
0 missing
a_59numeric2 unique values
0 missing
a_60numeric2 unique values
0 missing
a_61numeric2 unique values
0 missing
a_62numeric2 unique values
0 missing
a_63numeric2 unique values
0 missing
a_64numeric2 unique values
0 missing
a_65numeric2 unique values
0 missing
a_66numeric2 unique values
0 missing
a_67numeric2 unique values
0 missing
a_68numeric2 unique values
0 missing
a_69numeric2 unique values
0 missing
a_70numeric2 unique values
0 missing
a_71numeric2 unique values
0 missing
a_72numeric2 unique values
0 missing
a_73numeric2 unique values
0 missing
a_74numeric2 unique values
0 missing
a_75numeric2 unique values
0 missing
a_76numeric2 unique values
0 missing
a_77numeric2 unique values
0 missing
a_78numeric2 unique values
0 missing
a_79numeric2 unique values
0 missing
a_80numeric2 unique values
0 missing
a_81numeric2 unique values
0 missing
a_82numeric2 unique values
0 missing
a_83numeric2 unique values
0 missing
a_84numeric2 unique values
0 missing
a_85numeric2 unique values
0 missing
a_86numeric2 unique values
0 missing
a_87numeric2 unique values
0 missing
a_88numeric2 unique values
0 missing
a_89numeric2 unique values
0 missing
a_90numeric2 unique values
0 missing
a_91numeric2 unique values
0 missing
a_92numeric2 unique values
0 missing
a_93numeric2 unique values
0 missing
a_94numeric2 unique values
0 missing
a_95numeric2 unique values
0 missing
a_96numeric2 unique values
0 missing
a_97numeric2 unique values
0 missing
a_98numeric2 unique values
0 missing
a_99numeric2 unique values
0 missing
a_100numeric2 unique values
0 missing
a_101numeric2 unique values
0 missing
a_102numeric2 unique values
0 missing
a_103numeric2 unique values
0 missing
a_104numeric2 unique values
0 missing
a_105numeric2 unique values
0 missing
a_106numeric2 unique values
0 missing
a_107numeric2 unique values
0 missing
a_108numeric2 unique values
0 missing
a_109numeric2 unique values
0 missing
a_110numeric2 unique values
0 missing
a_111numeric2 unique values
0 missing
a_112numeric2 unique values
0 missing
a_113numeric2 unique values
0 missing
a_114numeric2 unique values
0 missing
a_115numeric2 unique values
0 missing
a_116numeric2 unique values
0 missing
a_117numeric2 unique values
0 missing
a_118numeric2 unique values
0 missing
a_119numeric2 unique values
0 missing
a_120numeric2 unique values
0 missing
a_121numeric2 unique values
0 missing
a_122numeric2 unique values
0 missing
a_123numeric2 unique values
0 missing
a_124numeric2 unique values
0 missing
a_125numeric2 unique values
0 missing
a_126numeric2 unique values
0 missing
a_127numeric2 unique values
0 missing
a_128numeric2 unique values
0 missing
a_129numeric2 unique values
0 missing
a_130numeric2 unique values
0 missing
a_131numeric2 unique values
0 missing
a_132numeric2 unique values
0 missing
a_133numeric2 unique values
0 missing
a_134numeric2 unique values
0 missing
a_135numeric2 unique values
0 missing
a_136numeric2 unique values
0 missing
a_137numeric2 unique values
0 missing
a_138numeric2 unique values
0 missing
a_139numeric2 unique values
0 missing
a_140numeric2 unique values
0 missing
a_141numeric2 unique values
0 missing
a_142numeric2 unique values
0 missing
a_143numeric2 unique values
0 missing
a_144numeric2 unique values
0 missing
a_145numeric2 unique values
0 missing
a_146numeric2 unique values
0 missing
a_147numeric2 unique values
0 missing
a_148numeric2 unique values
0 missing
a_149numeric2 unique values
0 missing
a_150numeric2 unique values
0 missing
a_151numeric2 unique values
0 missing
a_152numeric2 unique values
0 missing
a_153numeric2 unique values
0 missing
a_154numeric2 unique values
0 missing
a_155numeric2 unique values
0 missing
a_156numeric2 unique values
0 missing
a_157numeric2 unique values
0 missing
a_158numeric2 unique values
0 missing
a_159numeric2 unique values
0 missing
a_160numeric2 unique values
0 missing
a_161numeric2 unique values
0 missing
a_162numeric2 unique values
0 missing
a_163numeric2 unique values
0 missing
a_164numeric2 unique values
0 missing
a_165numeric2 unique values
0 missing
a_166numeric2 unique values
0 missing
a_167numeric2 unique values
0 missing
a_168numeric2 unique values
0 missing
a_169numeric2 unique values
0 missing
a_170numeric2 unique values
0 missing
a_171numeric2 unique values
0 missing
a_172numeric2 unique values
0 missing
a_173numeric2 unique values
0 missing
a_174numeric2 unique values
0 missing
a_175numeric2 unique values
0 missing
a_176numeric2 unique values
0 missing
a_177numeric2 unique values
0 missing
a_178numeric2 unique values
0 missing
a_179numeric2 unique values
0 missing
a_180numeric2 unique values
0 missing
a_181numeric2 unique values
0 missing
a_182numeric2 unique values
0 missing
a_183numeric2 unique values
0 missing
a_184numeric2 unique values
0 missing
a_185numeric2 unique values
0 missing
a_186numeric2 unique values
0 missing
a_187numeric2 unique values
0 missing
a_188numeric2 unique values
0 missing
a_189numeric2 unique values
0 missing
a_190numeric2 unique values
0 missing
a_191numeric2 unique values
0 missing
a_192numeric2 unique values
0 missing
a_193numeric2 unique values
0 missing
a_194numeric2 unique values
0 missing
a_195numeric2 unique values
0 missing
a_196numeric2 unique values
0 missing
a_197numeric2 unique values
0 missing
a_198numeric2 unique values
0 missing
a_199numeric2 unique values
0 missing
a_200numeric2 unique values
0 missing
a_201numeric2 unique values
0 missing
a_202numeric2 unique values
0 missing
a_203numeric2 unique values
0 missing
a_204numeric2 unique values
0 missing
a_205numeric2 unique values
0 missing
a_206numeric2 unique values
0 missing
a_207numeric2 unique values
0 missing
a_208numeric2 unique values
0 missing
a_209numeric2 unique values
0 missing
a_210numeric2 unique values
0 missing
a_211numeric2 unique values
0 missing
a_212numeric2 unique values
0 missing
a_213numeric2 unique values
0 missing
a_214numeric2 unique values
0 missing
a_215numeric2 unique values
0 missing
a_216numeric2 unique values
0 missing
a_217numeric2 unique values
0 missing
a_218numeric2 unique values
0 missing
a_219numeric2 unique values
0 missing
a_220numeric2 unique values
0 missing
a_221numeric2 unique values
0 missing
a_222numeric2 unique values
0 missing
a_223numeric2 unique values
0 missing
a_224numeric2 unique values
0 missing
a_225numeric2 unique values
0 missing
a_226numeric2 unique values
0 missing
a_227numeric2 unique values
0 missing
a_228numeric2 unique values
0 missing
a_229numeric2 unique values
0 missing
a_230numeric2 unique values
0 missing
a_231numeric2 unique values
0 missing
a_232numeric2 unique values
0 missing
a_233numeric2 unique values
0 missing
a_234numeric2 unique values
0 missing
a_235numeric2 unique values
0 missing
a_236numeric2 unique values
0 missing
a_237numeric2 unique values
0 missing
a_238numeric2 unique values
0 missing
a_239numeric2 unique values
0 missing
a_240numeric2 unique values
0 missing
a_241numeric2 unique values
0 missing
a_242numeric2 unique values
0 missing
a_243numeric2 unique values
0 missing
a_244numeric2 unique values
0 missing
a_245numeric2 unique values
0 missing
a_246numeric2 unique values
0 missing
a_247numeric2 unique values
0 missing
a_248numeric2 unique values
0 missing
a_249numeric2 unique values
0 missing
a_250numeric2 unique values
0 missing
a_251numeric2 unique values
0 missing
a_252numeric2 unique values
0 missing
a_253numeric2 unique values
0 missing
a_254numeric2 unique values
0 missing
a_255numeric2 unique values
0 missing

62 properties

1116
Number of instances (rows) of the dataset.
257
Number of attributes (columns) of the dataset.
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.
0.43
First quartile of skewness among attributes of the numeric type.
0.33
Mean of means among attributes of the numeric type.
0.44
First quartile of standard deviation of attributes of the numeric type.
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
Second quartile (Median) of entropy among attributes.
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.
-1.45
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.23
Number of attributes divided by the number of instances.
10
Average number of distinct values among the attributes of the nominal type.
0.33
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.
0.8
Mean skewness among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Percentage of instances belonging to the most frequent class.
0.46
Mean standard deviation of attributes of the numeric type.
0.74
Second quartile (Median) of skewness among attributes of the numeric type.
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
0
Percentage of binary attributes.
0.47
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
-2
Minimum kurtosis among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
19.4
Maximum kurtosis among attributes of the numeric type.
0.04
Minimum of means among attributes of the numeric type.
0
Percentage of missing values.
-0.79
Third quartile of kurtosis among attributes of the numeric type.
0.67
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.
0.39
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.
-0.73
Minimum skewness among attributes of the numeric type.
First quartile of entropy among attributes.
1.1
Third quartile of skewness among attributes of the numeric type.
4.62
Maximum skewness among attributes of the numeric type.
0.2
Minimum standard deviation of attributes of the numeric type.
-1.78
First quartile of kurtosis among attributes of the numeric type.
0.49
Third quartile of standard deviation of attributes of the numeric type.
0.5
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
0.26
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.
0
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
-0.97
Mean kurtosis among attributes of the numeric type.

16 tasks

0 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: class
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
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