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Author: Source: Unknown - Date unknown Please cite: Data from the RSCTC 2010 Discovery Challenge. All datasets contain between 100 and 400 samples, characterized by values of 20,000 - 65,000 attributes. Samples are assigned to several (2-10) classes. All attributes are numeric and represent measurements from DNA microarrays. Attributes are normalized in some way - in test data you should expect similar distributions of attribute values as in the example data. Source: http://tunedit.org/challenge/RSCTC-2010-A

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Var43963numeric184 unique values
0 missing
Var43964numeric156 unique values
0 missing
Var43965numeric175 unique values
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Var43966numeric160 unique values
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Var43967numeric143 unique values
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Var43968numeric150 unique values
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Var43970numeric177 unique values
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Var43971numeric159 unique values
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Var43973numeric157 unique values
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Var43974numeric155 unique values
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Var43977numeric163 unique values
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Var43983numeric157 unique values
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Var43989numeric173 unique values
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Var43990numeric172 unique values
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Var43991numeric142 unique values
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Var43992numeric157 unique values
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Var43993numeric169 unique values
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Var43994numeric153 unique values
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Var43995numeric187 unique values
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Var43996numeric199 unique values
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Var43998numeric129 unique values
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Var44001numeric163 unique values
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Var44002numeric147 unique values
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Var44003numeric176 unique values
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Var44004numeric155 unique values
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Var44005numeric178 unique values
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Var44006numeric143 unique values
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Var44007numeric183 unique values
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Var44008numeric172 unique values
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Var44009numeric166 unique values
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Var44010numeric180 unique values
0 missing
Var44011numeric127 unique values
0 missing
Var44012numeric200 unique values
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Var44013numeric144 unique values
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Var44014numeric149 unique values
0 missing
Var44015numeric157 unique values
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Var44016numeric148 unique values
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Var44017numeric183 unique values
0 missing
Var44018numeric153 unique values
0 missing
Var44019numeric146 unique values
0 missing
Var44020numeric147 unique values
0 missing
Var44021numeric133 unique values
0 missing
Var44022numeric155 unique values
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Var44023numeric179 unique values
0 missing
Var44024numeric132 unique values
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Var44025numeric183 unique values
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Var44026numeric194 unique values
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Var44027numeric161 unique values
0 missing
Var44028numeric174 unique values
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Var44029numeric196 unique values
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Var44030numeric164 unique values
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Var44031numeric184 unique values
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Var44032numeric183 unique values
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Var44033numeric167 unique values
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Var44036numeric153 unique values
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Var44046numeric156 unique values
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Var44047numeric191 unique values
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Var44049numeric143 unique values
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Var44050numeric160 unique values
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Var44051numeric184 unique values
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Var44058numeric162 unique values
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Var44059numeric157 unique values
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Var44060numeric153 unique values
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Var44063numeric156 unique values
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Var44085numeric151 unique values
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Var44086numeric164 unique values
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Var44087numeric167 unique values
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Var44089numeric143 unique values
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Var44091numeric138 unique values
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Var44093numeric159 unique values
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Var44094numeric157 unique values
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Var44095numeric157 unique values
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Var44096numeric140 unique values
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Var44098numeric192 unique values
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Var44099numeric174 unique values
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Var44100numeric165 unique values
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Var44101numeric144 unique values
0 missing
Var44102numeric163 unique values
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Var44103numeric184 unique values
0 missing
Var44104numeric151 unique values
0 missing
Var44105numeric155 unique values
0 missing
Var44106numeric199 unique values
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Var44107numeric151 unique values
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Var44108numeric169 unique values
0 missing
Var44109numeric191 unique values
0 missing
Var44110numeric173 unique values
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Var44112numeric181 unique values
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Var44113numeric166 unique values
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Var44114numeric144 unique values
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Var44115numeric168 unique values
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Var44116numeric148 unique values
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Var44117numeric141 unique values
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Var44118numeric160 unique values
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Var44119numeric149 unique values
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Var44120numeric147 unique values
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Var44121numeric157 unique values
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Var44122numeric148 unique values
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Var44123numeric198 unique values
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Var44124numeric152 unique values
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Var44125numeric152 unique values
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Var44126numeric156 unique values
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Var44127numeric155 unique values
0 missing
Var44128numeric160 unique values
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Var44129numeric169 unique values
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Var44130numeric192 unique values
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Var44131numeric142 unique values
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Var44132numeric188 unique values
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Var44133numeric161 unique values
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Var44134numeric163 unique values
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Var44135numeric180 unique values
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Var44136numeric171 unique values
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Var44137numeric164 unique values
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Var44138numeric130 unique values
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Var44139numeric156 unique values
0 missing
Var44140numeric177 unique values
0 missing
Var44141numeric142 unique values
0 missing
Var44142numeric150 unique values
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Var44143numeric189 unique values
0 missing
Var44144numeric136 unique values
0 missing
Var44145numeric143 unique values
0 missing
Var44146numeric166 unique values
0 missing
Var44147numeric142 unique values
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Var44148numeric136 unique values
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Var44149numeric144 unique values
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Var44150numeric168 unique values
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Var44151numeric157 unique values
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Var44152numeric136 unique values
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Var44153numeric189 unique values
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Var44154numeric191 unique values
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Var44155numeric172 unique values
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Var44156numeric158 unique values
0 missing
Var44157numeric149 unique values
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Var44158numeric164 unique values
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Var44159numeric166 unique values
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Var44160numeric189 unique values
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Var44161numeric151 unique values
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Var44162numeric184 unique values
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Var44163numeric149 unique values
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Var44164numeric171 unique values
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Var44165numeric186 unique values
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Var44166numeric128 unique values
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Var44168numeric197 unique values
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Var44169numeric185 unique values
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Var44170numeric176 unique values
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Var44171numeric184 unique values
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Var44172numeric154 unique values
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Var44173numeric165 unique values
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Var44174numeric185 unique values
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Var44175numeric184 unique values
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Var44176numeric181 unique values
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Var44177numeric138 unique values
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Var44178numeric183 unique values
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Var44179numeric186 unique values
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Var44182numeric150 unique values
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Var44183numeric180 unique values
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Var44184numeric171 unique values
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Var44185numeric144 unique values
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Var44186numeric174 unique values
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Var44187numeric157 unique values
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Var44188numeric165 unique values
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Var44189numeric156 unique values
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Var44190numeric152 unique values
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Var44191numeric167 unique values
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Var44192numeric143 unique values
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Var44193numeric171 unique values
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Var44194numeric152 unique values
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Var44196numeric154 unique values
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Var44197numeric176 unique values
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Var44198numeric151 unique values
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Var44199numeric171 unique values
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Var44200numeric127 unique values
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Var44201numeric160 unique values
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Var44202numeric204 unique values
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Var44203numeric191 unique values
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Var44204numeric151 unique values
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Var44205numeric153 unique values
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Var44206numeric154 unique values
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Var44208numeric205 unique values
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Var44209numeric186 unique values
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Var44210numeric184 unique values
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Var44211numeric153 unique values
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Var44212numeric147 unique values
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Var44213numeric184 unique values
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Var44214numeric162 unique values
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Var44215numeric189 unique values
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Var44216numeric156 unique values
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Var44217numeric190 unique values
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Var44218numeric174 unique values
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Var44219numeric127 unique values
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Var44220numeric157 unique values
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Var44221numeric157 unique values
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Var44222numeric158 unique values
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Var44223numeric174 unique values
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Var44224numeric174 unique values
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Var44225numeric172 unique values
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Var44227numeric150 unique values
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Var44228numeric181 unique values
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Var44241numeric135 unique values
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Var44247numeric179 unique values
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Var44248numeric188 unique values
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Var44249numeric184 unique values
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Var44250numeric148 unique values
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Var44251numeric152 unique values
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Var44252numeric159 unique values
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Var44253numeric163 unique values
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Var44254numeric181 unique values
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Var44255numeric176 unique values
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Var44256numeric163 unique values
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Var44257numeric162 unique values
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Var44258numeric138 unique values
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Var44259numeric159 unique values
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Var44260numeric164 unique values
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Var44261numeric178 unique values
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Var44262numeric165 unique values
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Var44263numeric174 unique values
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Var44264numeric143 unique values
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Var44265numeric161 unique values
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Var44266numeric151 unique values
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Var44267numeric158 unique values
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Var44268numeric189 unique values
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Var44269numeric169 unique values
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Var44270numeric164 unique values
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Var44271numeric180 unique values
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Var44272numeric142 unique values
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Var44273numeric155 unique values
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Var44274numeric142 unique values
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Var44275numeric164 unique values
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Var44276numeric171 unique values
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Var44277numeric152 unique values
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Var44278numeric184 unique values
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Var44279numeric156 unique values
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Var44280numeric168 unique values
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Var44281numeric179 unique values
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Var44282numeric135 unique values
0 missing
Var44283numeric158 unique values
0 missing
Var44284numeric132 unique values
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Var44285numeric143 unique values
0 missing
Var44286numeric146 unique values
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Var44287numeric172 unique values
0 missing
Var44288numeric171 unique values
0 missing
Var44289numeric130 unique values
0 missing
Var44290numeric138 unique values
0 missing
Var44291numeric145 unique values
0 missing
Var44292numeric181 unique values
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Var44293numeric161 unique values
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Var44294numeric142 unique values
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Var44295numeric175 unique values
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Var44296numeric157 unique values
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Var44297numeric164 unique values
0 missing
Var44298numeric152 unique values
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Var44299numeric179 unique values
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Var44300numeric178 unique values
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Var44301numeric144 unique values
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Var44302numeric158 unique values
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Var44303numeric157 unique values
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Var44304numeric173 unique values
0 missing
Var44305numeric190 unique values
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Var44306numeric120 unique values
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Var44307numeric187 unique values
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Var44308numeric183 unique values
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Var44309numeric157 unique values
0 missing
Var44310numeric159 unique values
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Var44311numeric150 unique values
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Var44312numeric130 unique values
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Var44313numeric175 unique values
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Var44314numeric172 unique values
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Var44315numeric151 unique values
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Var44316numeric196 unique values
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Var44317numeric187 unique values
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Var44318numeric186 unique values
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Var44319numeric154 unique values
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Var44320numeric162 unique values
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Var44321numeric181 unique values
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Var44322numeric165 unique values
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Var44323numeric154 unique values
0 missing
Var44324numeric130 unique values
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Var44325numeric161 unique values
0 missing
Var44326numeric195 unique values
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Var44327numeric181 unique values
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Var44328numeric148 unique values
0 missing
Var44329numeric154 unique values
0 missing
Var44330numeric156 unique values
0 missing
Var44331numeric160 unique values
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Var44332numeric169 unique values
0 missing
Var44333numeric175 unique values
0 missing
Var44334numeric175 unique values
0 missing
Var44335numeric143 unique values
0 missing
Var44336numeric175 unique values
0 missing
Var44337numeric170 unique values
0 missing
Var44338numeric158 unique values
0 missing
Var44339numeric142 unique values
0 missing
Var44340numeric145 unique values
0 missing
Var44341numeric167 unique values
0 missing
Var44342numeric174 unique values
0 missing
Var44343numeric161 unique values
0 missing
Var44344numeric153 unique values
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Var44345numeric159 unique values
0 missing
Var44346numeric171 unique values
0 missing
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Var44348numeric182 unique values
0 missing
Show first 100 features

107 properties

NumberOfInstances
214
Number of instances (rows) of the dataset.
NumberOfFeatures
45102
Number of attributes (columns) of the dataset.
NumberOfClasses
7
Number of distinct values of the target attribute (if it is nominal).
NumberOfMissingValues
0
Number of missing values in the dataset.
NumberOfInstancesWithMissingValues
0
Number of instances with at least one value missing.
NumberOfNumericFeatures
45101
Number of numeric attributes.
NumberOfSymbolicFeatures
1
Number of nominal attributes.
AutoCorrelation
0.15
Average class difference between consecutive instances.
CfsSubsetEval_DecisionStumpAUC
0.71
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
CfsSubsetEval_DecisionStumpErrRate
0.49
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
CfsSubsetEval_DecisionStumpKappa
0.39
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
CfsSubsetEval_NaiveBayesAUC
0.71
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
CfsSubsetEval_NaiveBayesErrRate
0.49
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
CfsSubsetEval_NaiveBayesKappa
0.39
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
CfsSubsetEval_kNN1NAUC
0.71
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
CfsSubsetEval_kNN1NErrRate
0.49
Error rate achieved by the landmarker weka.classifiers.lazy.IBk -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
CfsSubsetEval_kNN1NKappa
0.39
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
ClassEntropy
2.58
Entropy of the target attribute values.
DecisionStumpAUC
0.64
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpErrRate
0.61
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpKappa
0.18
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
Dimensionality
210.76
Number of attributes divided by the number of instances.
EquivalentNumberOfAtts
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
J48.00001.AUC
0.7
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.ErrRate
0.5
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.Kappa
0.38
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.0001.AUC
0.7
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.ErrRate
0.5
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.Kappa
0.38
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.001.AUC
0.7
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.ErrRate
0.5
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.Kappa
0.38
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
MajorityClassPercentage
32.24
Percentage of instances belonging to the most frequent class.
MajorityClassSize
69
Number of instances belonging to the most frequent class.
MaxAttributeEntropy
Maximum entropy among attributes.
MaxKurtosisOfNumericAtts
152.29
Maximum kurtosis among attributes of the numeric type.
MaxMeansOfNumericAtts
6.32
Maximum of means among attributes of the numeric type.
MaxMutualInformation
Maximum mutual information between the nominal attributes and the target attribute.
MaxNominalAttDistinctValues
7
The maximum number of distinct values among attributes of the nominal type.
MaxSkewnessOfNumericAtts
11.37
Maximum skewness among attributes of the numeric type.
MaxStdDevOfNumericAtts
1.55
Maximum standard deviation of attributes of the numeric type.
MeanAttributeEntropy
Average entropy of the attributes.
MeanKurtosisOfNumericAtts
0.97
Mean kurtosis among attributes of the numeric type.
MeanMeansOfNumericAtts
2.39
Mean of means among attributes of the numeric type.
MeanMutualInformation
Average mutual information between the nominal attributes and the target attribute.
MeanNoiseToSignalRatio
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
MeanNominalAttDistinctValues
7
Average number of distinct values among the attributes of the nominal type.
MeanSkewnessOfNumericAtts
0.25
Mean skewness among attributes of the numeric type.
MeanStdDevOfNumericAtts
0.16
Mean standard deviation of attributes of the numeric type.
MinAttributeEntropy
Minimal entropy among attributes.
MinKurtosisOfNumericAtts
-1.69
Minimum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
1.06
Minimum of means among attributes of the numeric type.
MinMutualInformation
Minimal mutual information between the nominal attributes and the target attribute.
MinNominalAttDistinctValues
7
The minimal number of distinct values among attributes of the nominal type.
MinSkewnessOfNumericAtts
-4.45
Minimum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
0.04
Minimum standard deviation of attributes of the numeric type.
MinorityClassPercentage
6.07
Percentage of instances belonging to the least frequent class.
MinorityClassSize
13
Number of instances belonging to the least frequent class.
NaiveBayesAUC
0.73
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesErrRate
0.43
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesKappa
0.46
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NumberOfBinaryFeatures
0
Number of binary attributes.
PercentageOfBinaryFeatures
0
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
PercentageOfMissingValues
0
Percentage of missing values.
PercentageOfNumericFeatures
100
Percentage of numeric attributes.
PercentageOfSymbolicFeatures
0
Percentage of nominal attributes.
Quartile1AttributeEntropy
First quartile of entropy among attributes.
Quartile1KurtosisOfNumericAtts
0.03
First quartile of kurtosis among attributes of the numeric type.
Quartile1MeansOfNumericAtts
1.6
First quartile of means among attributes of the numeric type.
Quartile1MutualInformation
First quartile of mutual information between the nominal attributes and the target attribute.
Quartile1SkewnessOfNumericAtts
-0.11
First quartile of skewness among attributes of the numeric type.
Quartile1StdDevOfNumericAtts
0.08
First quartile of standard deviation of attributes of the numeric type.
Quartile2AttributeEntropy
Second quartile (Median) of entropy among attributes.
Quartile2KurtosisOfNumericAtts
0.49
Second quartile (Median) of kurtosis among attributes of the numeric type.
Quartile2MeansOfNumericAtts
2.12
Second quartile (Median) of means among attributes of the numeric type.
Quartile2MutualInformation
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Quartile2SkewnessOfNumericAtts
0.28
Second quartile (Median) of skewness among attributes of the numeric type.
Quartile2StdDevOfNumericAtts
0.11
Second quartile (Median) of standard deviation of attributes of the numeric type.
Quartile3AttributeEntropy
Third quartile of entropy among attributes.
Quartile3KurtosisOfNumericAtts
1.21
Third quartile of kurtosis among attributes of the numeric type.
Quartile3MeansOfNumericAtts
3.02
Third quartile of means among attributes of the numeric type.
Quartile3MutualInformation
Third quartile of mutual information between the nominal attributes and the target attribute.
Quartile3SkewnessOfNumericAtts
0.63
Third quartile of skewness among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
0.19
Third quartile of standard deviation of attributes of the numeric type.
REPTreeDepth1AUC
0.75
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1ErrRate
0.44
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1Kappa
0.44
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth2AUC
0.75
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2ErrRate
0.44
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2Kappa
0.44
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth3AUC
0.75
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3ErrRate
0.44
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3Kappa
0.44
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
RandomTreeDepth1AUC
0.63
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1ErrRate
0.61
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1Kappa
0.25
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth2AUC
0.63
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2ErrRate
0.61
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2Kappa
0.25
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth3AUC
0.63
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3ErrRate
0.61
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3Kappa
0.25
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
StdvNominalAttDistinctValues
0
Standard deviation of the number of distinct values among attributes of the nominal type.
kNN1NAUC
0.77
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NErrRate
0.39
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NKappa
0.52
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
Show all 107 properties

14 tasks

Supervised Classification on mouseType
10 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: Decision
Supervised Classification on mouseType
1 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: Decision
Supervised Data Stream Classification on mouseType
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: Decision
Clustering on mouseType
0 runs
Clustering on mouseType
0 runs - estimation_procedure: 50 times Clustering
Clustering on mouseType
0 runs - estimation_procedure: 50 times Clustering
Clustering on mouseType
0 runs - estimation_procedure: 50 times Clustering
Clustering on mouseType
0 runs - estimation_procedure: 50 times Clustering
Clustering on mouseType
0 runs - estimation_procedure: 50 times Clustering
Clustering on mouseType
0 runs - estimation_procedure: 50 times Clustering
Clustering on mouseType
0 runs - estimation_procedure: 50 times Clustering
Clustering on mouseType
0 runs - estimation_procedure: 50 times Clustering
Clustering on mouseType
0 runs - estimation_procedure: 50 times Clustering
Clustering on mouseType
0 runs - estimation_procedure: 50 times Clustering
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