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reuters

reuters

active ARFF Publicly available Visibility: public Uploaded 14-03-2019 by Quay Au
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  • 2019_multioutput_paper Social Media Statistics
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Multi-label dataset. A subset of the reuters dataset includes 2000 observations for text classification.

250 features

label1 (target)nominal2 unique values
0 missing
label2 (target)nominal2 unique values
0 missing
label3 (target)nominal2 unique values
0 missing
label4 (target)nominal2 unique values
0 missing
label5 (target)nominal2 unique values
0 missing
label6 (target)nominal2 unique values
0 missing
label7 (target)nominal2 unique values
0 missing
feature1numeric8 unique values
0 missing
feature2numeric4 unique values
0 missing
feature3numeric4 unique values
0 missing
feature4numeric7 unique values
0 missing
feature5numeric14 unique values
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feature6numeric15 unique values
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feature7numeric23 unique values
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feature8numeric13 unique values
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feature9numeric24 unique values
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feature10numeric15 unique values
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feature11numeric19 unique values
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feature12numeric15 unique values
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feature13numeric22 unique values
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feature14numeric12 unique values
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feature15numeric22 unique values
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feature16numeric17 unique values
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feature17numeric15 unique values
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feature18numeric10 unique values
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feature19numeric23 unique values
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feature20numeric10 unique values
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feature21numeric17 unique values
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feature22numeric20 unique values
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feature23numeric15 unique values
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feature24numeric8 unique values
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feature25numeric18 unique values
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feature26numeric11 unique values
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feature27numeric12 unique values
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feature28numeric15 unique values
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feature29numeric15 unique values
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feature30numeric9 unique values
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feature31numeric22 unique values
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feature32numeric13 unique values
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feature33numeric10 unique values
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feature34numeric16 unique values
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feature35numeric8 unique values
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feature36numeric15 unique values
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feature37numeric16 unique values
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feature38numeric9 unique values
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feature39numeric11 unique values
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feature40numeric14 unique values
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feature41numeric11 unique values
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feature42numeric6 unique values
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feature43numeric16 unique values
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feature44numeric8 unique values
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feature45numeric14 unique values
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feature46numeric18 unique values
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feature47numeric11 unique values
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feature48numeric7 unique values
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feature49numeric14 unique values
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feature50numeric16 unique values
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feature51numeric12 unique values
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feature52numeric10 unique values
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feature53numeric9 unique values
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feature54numeric7 unique values
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feature55numeric10 unique values
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feature56numeric14 unique values
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feature57numeric13 unique values
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feature58numeric12 unique values
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feature59numeric10 unique values
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feature60numeric9 unique values
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feature61numeric17 unique values
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feature62numeric10 unique values
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feature63numeric7 unique values
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feature64numeric15 unique values
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feature65numeric10 unique values
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feature66numeric10 unique values
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feature67numeric16 unique values
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feature68numeric7 unique values
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feature69numeric8 unique values
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feature70numeric8 unique values
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feature71numeric15 unique values
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feature72numeric6 unique values
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feature73numeric10 unique values
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feature74numeric8 unique values
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feature75numeric5 unique values
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feature76numeric11 unique values
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feature77numeric14 unique values
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feature78numeric16 unique values
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feature79numeric10 unique values
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feature80numeric8 unique values
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feature81numeric15 unique values
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feature82numeric7 unique values
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feature83numeric7 unique values
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feature84numeric6 unique values
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feature85numeric16 unique values
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feature86numeric11 unique values
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feature87numeric6 unique values
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feature88numeric7 unique values
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feature89numeric16 unique values
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feature90numeric7 unique values
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feature91numeric12 unique values
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feature92numeric12 unique values
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feature93numeric7 unique values
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feature94numeric8 unique values
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feature95numeric6 unique values
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feature96numeric11 unique values
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feature97numeric10 unique values
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feature98numeric7 unique values
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feature99numeric12 unique values
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feature100numeric9 unique values
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feature101numeric11 unique values
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feature102numeric6 unique values
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feature103numeric9 unique values
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feature104numeric8 unique values
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feature105numeric8 unique values
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feature106numeric18 unique values
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feature107numeric8 unique values
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feature108numeric7 unique values
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feature109numeric9 unique values
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feature110numeric7 unique values
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feature111numeric11 unique values
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feature112numeric7 unique values
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feature113numeric13 unique values
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feature114numeric7 unique values
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feature115numeric14 unique values
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feature116numeric7 unique values
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feature117numeric7 unique values
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feature118numeric10 unique values
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feature119numeric9 unique values
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feature120numeric10 unique values
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feature121numeric13 unique values
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feature122numeric10 unique values
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feature123numeric6 unique values
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feature124numeric6 unique values
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feature125numeric9 unique values
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feature126numeric8 unique values
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feature127numeric14 unique values
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feature128numeric5 unique values
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feature129numeric5 unique values
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feature130numeric9 unique values
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feature131numeric9 unique values
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feature132numeric5 unique values
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feature133numeric13 unique values
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feature134numeric15 unique values
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feature135numeric6 unique values
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feature136numeric9 unique values
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feature137numeric9 unique values
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feature138numeric5 unique values
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feature139numeric8 unique values
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feature140numeric5 unique values
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feature141numeric14 unique values
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feature142numeric7 unique values
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feature143numeric6 unique values
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feature144numeric8 unique values
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feature145numeric10 unique values
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feature146numeric7 unique values
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feature147numeric6 unique values
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feature148numeric11 unique values
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feature149numeric8 unique values
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feature150numeric6 unique values
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feature151numeric9 unique values
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feature152numeric6 unique values
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feature153numeric11 unique values
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feature154numeric11 unique values
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feature155numeric10 unique values
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feature156numeric9 unique values
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feature157numeric7 unique values
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feature158numeric5 unique values
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feature159numeric7 unique values
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feature160numeric5 unique values
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feature161numeric11 unique values
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feature162numeric8 unique values
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feature163numeric10 unique values
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feature164numeric7 unique values
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feature165numeric7 unique values
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feature166numeric7 unique values
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feature167numeric6 unique values
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feature168numeric5 unique values
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feature169numeric15 unique values
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feature170numeric5 unique values
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feature171numeric12 unique values
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feature172numeric13 unique values
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feature173numeric9 unique values
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feature174numeric6 unique values
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feature175numeric7 unique values
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feature176numeric9 unique values
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feature177numeric7 unique values
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feature178numeric5 unique values
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feature179numeric6 unique values
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feature180numeric6 unique values
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feature181numeric9 unique values
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feature182numeric6 unique values
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feature183numeric6 unique values
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feature184numeric5 unique values
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feature185numeric8 unique values
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feature186numeric6 unique values
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feature187numeric9 unique values
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feature188numeric9 unique values
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feature189numeric7 unique values
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feature190numeric10 unique values
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feature191numeric13 unique values
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feature192numeric6 unique values
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feature193numeric11 unique values
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feature194numeric7 unique values
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feature195numeric7 unique values
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feature196numeric10 unique values
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feature197numeric10 unique values
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feature198numeric6 unique values
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feature199numeric8 unique values
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feature200numeric5 unique values
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feature201numeric9 unique values
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feature202numeric6 unique values
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feature203numeric5 unique values
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feature204numeric6 unique values
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feature205numeric12 unique values
0 missing
feature206numeric7 unique values
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feature207numeric7 unique values
0 missing
feature208numeric10 unique values
0 missing
feature209numeric7 unique values
0 missing
feature210numeric8 unique values
0 missing
feature211numeric14 unique values
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feature212numeric7 unique values
0 missing
feature213numeric5 unique values
0 missing
feature214numeric4 unique values
0 missing
feature215numeric5 unique values
0 missing
feature216numeric6 unique values
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feature217numeric8 unique values
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feature218numeric8 unique values
0 missing
feature219numeric4 unique values
0 missing
feature220numeric5 unique values
0 missing
feature221numeric11 unique values
0 missing
feature222numeric9 unique values
0 missing
feature223numeric8 unique values
0 missing
feature224numeric6 unique values
0 missing
feature225numeric11 unique values
0 missing
feature226numeric10 unique values
0 missing
feature227numeric5 unique values
0 missing
feature228numeric5 unique values
0 missing
feature229numeric10 unique values
0 missing
feature230numeric5 unique values
0 missing
feature231numeric6 unique values
0 missing
feature232numeric10 unique values
0 missing
feature233numeric7 unique values
0 missing
feature234numeric6 unique values
0 missing
feature235numeric9 unique values
0 missing
feature236numeric7 unique values
0 missing
feature237numeric6 unique values
0 missing
feature238numeric5 unique values
0 missing
feature239numeric9 unique values
0 missing
feature240numeric4 unique values
0 missing
feature241numeric12 unique values
0 missing
feature242numeric6 unique values
0 missing
feature243numeric7 unique values
0 missing

62 properties

2000
Number of instances (rows) of the dataset.
250
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.
243
Number of numeric attributes.
7
Number of nominal 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.
Second quartile (Median) of entropy among attributes.
0.13
Number of attributes divided by the number of instances.
2
Average number of distinct values among the attributes of the nominal type.
67.43
Second quartile (Median) of kurtosis 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.
8.2
Mean skewness among attributes of the numeric type.
0.14
Second quartile (Median) of means among attributes of the numeric type.
Percentage of instances belonging to the most frequent class.
0.8
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
7.14
Second quartile (Median) of skewness among attributes of the numeric type.
Maximum entropy among attributes.
-1.61
Minimum kurtosis among attributes of the numeric type.
2.8
Percentage of binary attributes.
0.66
Second quartile (Median) of standard deviation of attributes of the numeric type.
1138.79
Maximum kurtosis among attributes of the numeric type.
0.04
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
1.3
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of missing values.
140.38
Third quartile of kurtosis among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
2
The minimal number of distinct values among attributes of the nominal type.
97.2
Percentage of numeric attributes.
0.24
Third quartile of means among attributes of the numeric type.
2
The maximum number of distinct values among attributes of the nominal type.
0.06
Minimum skewness among attributes of the numeric type.
2.8
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
30.17
Maximum skewness among attributes of the numeric type.
0.26
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
9.53
Third quartile of skewness among attributes of the numeric type.
2.78
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
41.96
First quartile of kurtosis among attributes of the numeric type.
1.01
Third quartile of standard deviation of attributes of the numeric type.
Average entropy of the attributes.
Number of instances belonging to the least frequent class.
0.1
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.
121.43
Mean kurtosis among attributes of the numeric type.
7
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
0.22
Mean of means among attributes of the numeric type.
5.58
First quartile of skewness among attributes of the numeric type.
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
0.46
First quartile of standard deviation of attributes of the numeric type.

9 tasks

0 runs - estimation_procedure: 50 times Clustering
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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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