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Amazon-test

Amazon-test

in_preparation ARFF Publicly available Visibility: public Uploaded 20-06-2017 by Stefan Coors
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Source: Dataset creator and donator: ZhiLiu, e-mail: liuzhi8673 '@' gmail.com, institution: National Engineering Research Center for E-Learning, Hubei Wuhan, China Data Set Information: dataset are derived from the customers’ reviews in Amazon Commerce Website for authorship identification. Most previous studies conducted the identification experiments for two to ten authors. But in the online context, reviews to be identified usually have more potential authors, and normally classification algorithms are not adapted to large number of target classes. To examine the robustness of clasification algorithms, we identified 50 of the most active users (represented by a unique ID and username) who frequently posted reviews in these newsgroups. The number of reviews we collected for each author is 30. Attribute Information: attribution includes authors' lingustic style such as usage of digit, punctuation, words and sentences' length and usage frequency of words and so on #autoxgboost #autoweka

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0 missing
a_2318numeric2 unique values
0 missing
a_2574numeric3 unique values
0 missing
a_2830numeric2 unique values
0 missing
a_3086numeric2 unique values
0 missing
a_3342numeric3 unique values
0 missing
a_3598numeric5 unique values
0 missing
a_3854numeric3 unique values
0 missing
a_4110numeric2 unique values
0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
a_6670numeric16 unique values
0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
a_527numeric3 unique values
0 missing
a_783numeric3 unique values
0 missing
a_1039numeric3 unique values
0 missing
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0 missing
a_1551numeric3 unique values
0 missing
a_1807numeric3 unique values
0 missing
a_2063numeric3 unique values
0 missing
a_2319numeric2 unique values
0 missing
a_2575numeric2 unique values
0 missing
a_2831numeric2 unique values
0 missing
a_3087numeric2 unique values
0 missing
a_3343numeric2 unique values
0 missing
a_3599numeric4 unique values
0 missing
a_3855numeric2 unique values
0 missing
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0 missing
a_4367numeric3 unique values
0 missing
a_4623numeric2 unique values
0 missing
a_4879numeric2 unique values
0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
a_6415numeric2 unique values
0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
a_528numeric6 unique values
0 missing
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0 missing
a_1040numeric4 unique values
0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
a_3344numeric2 unique values
0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
a_4880numeric2 unique values
0 missing
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0 missing
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0 missing
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0 missing
a_5904numeric2 unique values
0 missing
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0 missing
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0 missing
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0 missing
a_6928numeric12 unique values
0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
a_9488numeric6 unique values
0 missing
a_9744numeric3 unique values
0 missing
classnominal50 unique values
0 missing
a_17numeric9 unique values
0 missing
a_273numeric3 unique values
0 missing
a_529numeric3 unique values
0 missing
a_785numeric2 unique values
0 missing
a_1041numeric4 unique values
0 missing
a_1297numeric3 unique values
0 missing
a_1553numeric2 unique values
0 missing
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0 missing
a_2065numeric2 unique values
0 missing
a_2321numeric3 unique values
0 missing
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0 missing
a_2833numeric2 unique values
0 missing
a_3089numeric2 unique values
0 missing
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0 missing
a_3601numeric3 unique values
0 missing
a_3857numeric4 unique values
0 missing
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0 missing
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0 missing
a_4625numeric2 unique values
0 missing
a_4881numeric2 unique values
0 missing
a_5137numeric2 unique values
0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
a_6929numeric10 unique values
0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
a_3347numeric2 unique values
0 missing
a_3603numeric4 unique values
0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
a_6675numeric17 unique values
0 missing
a_6931numeric9 unique values
0 missing
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0 missing
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0 missing
a_7699numeric10 unique values
0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
a_9747numeric5 unique values
0 missing
a_20numeric6 unique values
0 missing
a_276numeric3 unique values
0 missing
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0 missing
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0 missing
a_1044numeric4 unique values
0 missing
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0 missing
a_1556numeric2 unique values
0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
a_21numeric10 unique values
0 missing
a_277numeric3 unique values
0 missing
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0 missing
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0 missing
a_1045numeric2 unique values
0 missing
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0 missing
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0 missing
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0 missing
a_2069numeric5 unique values
0 missing
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0 missing
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0 missing
a_2837numeric3 unique values
0 missing
a_3093numeric2 unique values
0 missing
a_3349numeric3 unique values
0 missing
a_3605numeric5 unique values
0 missing
a_3861numeric2 unique values
0 missing
a_4117numeric2 unique values
0 missing
a_4373numeric2 unique values
0 missing
a_4629numeric2 unique values
0 missing
a_4885numeric2 unique values
0 missing
a_5141numeric2 unique values
0 missing
a_5397numeric2 unique values
0 missing
a_5653numeric2 unique values
0 missing
a_5909numeric2 unique values
0 missing
a_6165numeric2 unique values
0 missing
a_6421numeric2 unique values
0 missing
a_6677numeric16 unique values
0 missing
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0 missing
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0 missing
a_7445numeric9 unique values
0 missing
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0 missing
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0 missing
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0 missing
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0 missing
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0 missing
a_8981numeric5 unique values
0 missing
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0 missing
a_9493numeric4 unique values
0 missing
a_9749numeric4 unique values
0 missing
a_22numeric8 unique values
0 missing
a_278numeric4 unique values
0 missing
a_534numeric4 unique values
0 missing
a_790numeric3 unique values
0 missing
a_1046numeric3 unique values
0 missing
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0 missing
a_1558numeric3 unique values
0 missing
a_1814numeric2 unique values
0 missing
a_2070numeric3 unique values
0 missing
a_2326numeric3 unique values
0 missing
a_2582numeric3 unique values
0 missing
a_2838numeric2 unique values
0 missing
a_3094numeric2 unique values
0 missing
a_3350numeric3 unique values
0 missing
a_3606numeric3 unique values
0 missing
a_3862numeric3 unique values
0 missing
a_4118numeric2 unique values
0 missing
a_4374numeric2 unique values
0 missing
a_4630numeric2 unique values
0 missing
a_4886numeric2 unique values
0 missing
a_5142numeric2 unique values
0 missing
a_5398numeric2 unique values
0 missing
a_5654numeric2 unique values
0 missing
a_5910numeric2 unique values
0 missing
a_6166numeric3 unique values
0 missing
a_6422numeric2 unique values
0 missing
a_6678numeric17 unique values
0 missing
a_6934numeric15 unique values
0 missing
a_7190numeric7 unique values
0 missing
a_7446numeric6 unique values
0 missing
a_7702numeric9 unique values
0 missing
a_7958numeric6 unique values
0 missing
a_8214numeric5 unique values
0 missing
a_8470numeric8 unique values
0 missing
a_8726numeric7 unique values
0 missing
a_8982numeric5 unique values
0 missing
a_9238numeric4 unique values
0 missing
a_9494numeric4 unique values
0 missing
a_9750numeric7 unique values
0 missing
a_23numeric8 unique values
0 missing
a_279numeric3 unique values
0 missing
a_535numeric3 unique values
0 missing
a_791numeric4 unique values
0 missing
a_1047numeric3 unique values
0 missing
a_1303numeric3 unique values
0 missing
a_1559numeric3 unique values
0 missing
a_1815numeric2 unique values
0 missing
a_2071numeric3 unique values
0 missing
a_2327numeric2 unique values
0 missing
a_2583numeric2 unique values
0 missing
a_2839numeric2 unique values
0 missing
a_3095numeric2 unique values
0 missing
a_3351numeric2 unique values
0 missing
a_3607numeric4 unique values
0 missing
a_3863numeric2 unique values
0 missing
a_4119numeric4 unique values
0 missing
a_4375numeric3 unique values
0 missing
a_4631numeric2 unique values
0 missing
a_4887numeric3 unique values
0 missing
a_5143numeric2 unique values
0 missing
a_5399numeric2 unique values
0 missing
a_5655numeric2 unique values
0 missing
a_5911numeric2 unique values
0 missing
a_6167numeric3 unique values
0 missing
a_6423numeric2 unique values
0 missing
a_6679numeric19 unique values
0 missing
a_6935numeric9 unique values
0 missing
a_7191numeric10 unique values
0 missing
a_7447numeric8 unique values
0 missing
a_7703numeric9 unique values
0 missing
a_7959numeric9 unique values
0 missing
a_8215numeric6 unique values
0 missing
a_8471numeric7 unique values
0 missing
a_8727numeric4 unique values
0 missing
a_8983numeric4 unique values
0 missing
a_9239numeric5 unique values
0 missing
a_9495numeric4 unique values
0 missing
a_9751numeric6 unique values
0 missing
a_24numeric7 unique values
0 missing
a_280numeric4 unique values
0 missing
a_536numeric4 unique values
0 missing
a_792numeric3 unique values
0 missing
a_1048numeric2 unique values
0 missing
a_1304numeric3 unique values
0 missing
a_1560numeric2 unique values
0 missing
a_1816numeric4 unique values
0 missing
a_2072numeric2 unique values
0 missing
a_2328numeric2 unique values
0 missing
a_2584numeric2 unique values
0 missing
a_2840numeric3 unique values
0 missing
a_3096numeric2 unique values
0 missing
a_3352numeric2 unique values
0 missing
a_3608numeric4 unique values
0 missing
a_3864numeric2 unique values
0 missing
a_4120numeric3 unique values
0 missing
a_4376numeric2 unique values
0 missing
a_4632numeric2 unique values
0 missing
a_4888numeric2 unique values
0 missing
a_5144numeric2 unique values
0 missing
a_5400numeric3 unique values
0 missing
a_5656numeric2 unique values
0 missing
a_5912numeric2 unique values
0 missing
a_6168numeric2 unique values
0 missing
a_6424numeric2 unique values
0 missing
a_6680numeric16 unique values
0 missing
a_6936numeric10 unique values
0 missing
a_7192numeric12 unique values
0 missing
a_7448numeric7 unique values
0 missing
a_7704numeric6 unique values
0 missing
a_7960numeric6 unique values
0 missing
a_8216numeric6 unique values
0 missing
a_8472numeric6 unique values
0 missing
a_8728numeric5 unique values
0 missing
a_8984numeric4 unique values
0 missing
a_9240numeric4 unique values
0 missing
a_9496numeric4 unique values
0 missing
a_9752numeric3 unique values
0 missing
a_25numeric8 unique values
0 missing
a_281numeric5 unique values
0 missing
a_537numeric4 unique values
0 missing
a_793numeric5 unique values
0 missing
a_1049numeric2 unique values
0 missing
a_1305numeric3 unique values
0 missing
a_1561numeric3 unique values
0 missing
a_1817numeric2 unique values
0 missing

62 properties

450
Number of instances (rows) of the dataset.
10001
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.
10000
Number of numeric attributes.
1
Number of nominal attributes.
2.74
First quartile of skewness among attributes of the numeric type.
0.41
Mean of means among attributes of the numeric type.
0.11
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.
48.8
Second quartile (Median) of kurtosis among attributes of the numeric type.
22.22
Number of attributes divided by the number of instances.
50
Average number of distinct values among the attributes of the nominal type.
0.03
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.
7.06
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.
0.49
Mean standard deviation of attributes of the numeric type.
6.88
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.
0.19
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
-0.8
Minimum kurtosis among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
450
Maximum kurtosis among attributes of the numeric type.
0
Minimum of means among attributes of the numeric type.
0
Percentage of missing values.
108.73
Third quartile of kurtosis among attributes of the numeric type.
249.72
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
99.99
Percentage of numeric attributes.
0.29
Third quartile of means among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
50
The minimal number of distinct values among attributes of the nominal type.
0.01
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
50
The maximum number of distinct values among attributes of the nominal type.
-0.43
Minimum skewness among attributes of the numeric type.
First quartile of entropy among attributes.
10.1
Third quartile of skewness among attributes of the numeric type.
21.21
Maximum skewness among attributes of the numeric type.
0
Minimum standard deviation of attributes of the numeric type.
9.62
First quartile of kurtosis among attributes of the numeric type.
0.64
Third quartile of standard deviation of attributes of the numeric type.
66.86
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.
0.01
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.
74.5
Mean kurtosis among attributes of the numeric type.

15 tasks

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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