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oh15.wc

oh15.wc

active Sparse_ARFF Publicly available Visibility: public Uploaded 28-09-2014 by Joaquin Vanschoren
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3101 features

CLASS_LABEL (target)nominal10 unique values
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clusternumeric3 unique values
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plainumeric4 unique values
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acutnumeric7 unique values
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densitinumeric7 unique values
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nucleinumeric3 unique values
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alnumeric10 unique values
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grownumeric4 unique values
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radicnumeric3 unique values
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reportnumeric7 unique values
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advancnumeric3 unique values
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intimnumeric4 unique values
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externnumeric4 unique values
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damagnumeric6 unique values
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infusnumeric4 unique values
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identifinumeric4 unique values
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accidnumeric2 unique values
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ownnumeric2 unique values
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parenchymnumeric2 unique values
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conjunctnumeric5 unique values
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csfnumeric9 unique values
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blotnumeric3 unique values
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killernumeric2 unique values
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respectnumeric6 unique values
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stenosnumeric3 unique values
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anionnumeric3 unique values
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chemicnumeric3 unique values
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orientnumeric3 unique values
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alternumeric5 unique values
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coronarinumeric9 unique values
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dopaminnumeric5 unique values
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nucleunumeric3 unique values
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atomnumeric4 unique values
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pathogenetnumeric3 unique values
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aequorinnumeric2 unique values
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analognumeric4 unique values
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batterinumeric3 unique values
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tssnumeric4 unique values
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phagocytosinumeric4 unique values
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drinknumeric4 unique values
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inputnumeric3 unique values
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thromboplastinnumeric5 unique values
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comparisonnumeric3 unique values
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insightnumeric2 unique values
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accumulnumeric7 unique values
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panumeric7 unique values
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destroinumeric2 unique values
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pcnumeric4 unique values
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callnumeric2 unique values
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reductasnumeric4 unique values
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proteinasnumeric3 unique values
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abnorma;numeric4 unique values
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pgnumeric4 unique values
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wechslernumeric3 unique values
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encountnumeric2 unique values
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introducnumeric3 unique values
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mealnumeric3 unique values
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quadricepnumeric2 unique values
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somewhnumeric2 unique values
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pkcnumeric12 unique values
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pnnumeric4 unique values
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reconstructnumeric4 unique values
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nephritinumeric4 unique values
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firnumeric2 unique values
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goalnumeric2 unique values
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hormonnumeric6 unique values
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exogennumeric5 unique values
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particularnumeric3 unique values
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choicenumeric3 unique values
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sufficinumeric2 unique values
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nonrespondnumeric4 unique values
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hydroxinumeric3 unique values
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amyloidnumeric7 unique values
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resectnumeric4 unique values
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fitnumeric2 unique values
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cathetnumeric10 unique values
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echocardiographinumeric3 unique values
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ileumnumeric3 unique values
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candidnumeric3 unique values
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fellnumeric3 unique values
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fixnumeric6 unique values
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sheathnumeric3 unique values
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pathophysiologinumeric2 unique values
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bpnumeric3 unique values
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unlabelnumeric3 unique values
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depolarnumeric4 unique values
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cuenumeric3 unique values
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forskolinnumeric5 unique values
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objectnumeric3 unique values
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destructnumeric2 unique values
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westernnumeric2 unique values
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0numeric32 unique values
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dodecylnumeric3 unique values
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vwfnumeric4 unique values
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availnumeric3 unique values
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distortnumeric2 unique values
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thrombinumeric4 unique values
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versionnumeric2 unique values
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dissectnumeric2 unique values
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gentamicinnumeric3 unique values
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sympathoadrennumeric4 unique values
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tyrosinnumeric9 unique values
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jurkatnumeric5 unique values
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innervnumeric3 unique values
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placemnumeric2 unique values
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vivonumeric7 unique values
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stagenumeric4 unique values
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seennumeric4 unique values
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movenumeric3 unique values
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rarenumeric4 unique values
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providnumeric3 unique values
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campnumeric9 unique values
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attendnumeric2 unique values
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aldosteronnumeric4 unique values
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mdanumeric4 unique values
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ablenumeric2 unique values
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julinumeric2 unique values
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bindernumeric3 unique values
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constrictnumeric4 unique values
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immunofluorescnumeric4 unique values
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particlnumeric5 unique values
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bunumeric2 unique values
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elastasnumeric4 unique values
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escherichianumeric3 unique values
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interrelnumeric2 unique values
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undergonnumeric2 unique values
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necropsinumeric2 unique values
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frenchnumeric3 unique values
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congenitnumeric3 unique values
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varietinumeric2 unique values
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gapnumeric4 unique values
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designnumeric3 unique values
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cervicnumeric3 unique values
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storagnumeric4 unique values
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ficollnumeric2 unique values
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redistributnumeric3 unique values
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rainumeric2 unique values
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osteomalacnumeric2 unique values
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repairnumeric6 unique values
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nickelnumeric2 unique values
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moda;numeric2 unique values
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cholinergnumeric2 unique values
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emphasnumeric2 unique values
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expensnumeric2 unique values
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changenumeric7 unique values
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mellitunumeric3 unique values
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obtainnumeric4 unique values
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trainnumeric5 unique values
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triggernumeric5 unique values
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dynamnumeric3 unique values
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tricuspidnumeric3 unique values
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magnetnumeric5 unique values
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satisfactorinumeric2 unique values
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unaffectnumeric3 unique values
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perceptunumeric3 unique values
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lineagnumeric3 unique values
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multivarinumeric3 unique values
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environnumeric2 unique values
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ambientnumeric3 unique values
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opticnumeric3 unique values
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actionnumeric7 unique values
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nephrectomnumeric3 unique values
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discussnumeric3 unique values
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demandnumeric3 unique values
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compromisnumeric2 unique values
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revealnumeric3 unique values
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pharmacolognumeric3 unique values
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attentnumeric4 unique values
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authornumeric3 unique values
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soundnumeric3 unique values
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polymorphonuclearnumeric3 unique values
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inablnumeric3 unique values
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phosphotyrosinnumeric3 unique values
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depletnumeric4 unique values
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virtualnumeric3 unique values
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allergennumeric3 unique values
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calcitoninnumeric4 unique values
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arthritinumeric5 unique values
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beamnumeric3 unique values
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resuscitnumeric4 unique values
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linearnumeric4 unique values
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confirmnumeric3 unique values
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concludnumeric2 unique values
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poorlinumeric3 unique values
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insolublnumeric3 unique values
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onsetnumeric4 unique values
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phosphatidylinositolnumeric3 unique values
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variatnumeric4 unique values
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blockadnumeric4 unique values
0 missing
goatenumeric2 unique values
0 missing
exclusnumeric2 unique values
0 missing
descriptnumeric2 unique values
0 missing
impactnumeric3 unique values
0 missing
stnumeric3 unique values
0 missing
rupturnumeric5 unique values
0 missing
bioactivnumeric3 unique values
0 missing
nitrogennumeric5 unique values
0 missing
warrantnumeric2 unique values
0 missing
primnumeric4 unique values
0 missing
vnumeric6 unique values
0 missing
dimernumeric5 unique values
0 missing
contraceptnumeric4 unique values
0 missing
antinuclearnumeric2 unique values
0 missing
stirnumeric3 unique values
0 missing
aliquotnumeric3 unique values
0 missing
discovnumeric2 unique values
0 missing
regularnumeric2 unique values
0 missing
dopplernumeric4 unique values
0 missing
immunosorbnumeric2 unique values
0 missing
fatenumeric4 unique values
0 missing
ischemnumeric6 unique values
0 missing
vasospasmnumeric2 unique values
0 missing
cerebellarnumeric4 unique values
0 missing
stimulunumeric3 unique values
0 missing
supplinumeric3 unique values
0 missing
terminunumeric2 unique values
0 missing
thoracnumeric2 unique values
0 missing
temperaturnumeric5 unique values
0 missing
highlinumeric3 unique values
0 missing
randomlinumeric2 unique values
0 missing
solublnumeric3 unique values
0 missing
balancnumeric6 unique values
0 missing
slowlinumeric2 unique values
0 missing
proceenumeric2 unique values
0 missing
blockagnumeric2 unique values
0 missing
introductnumeric2 unique values
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cationnumeric4 unique values
0 missing
regionnumeric6 unique values
0 missing
markernumeric5 unique values
0 missing
columnnumeric3 unique values
0 missing
compensnumeric3 unique values
0 missing
capdnumeric6 unique values
0 missing
benzodiazepinnumeric4 unique values
0 missing
thymocytnumeric3 unique values
0 missing
reminiscnumeric4 unique values
0 missing
managnumeric5 unique values
0 missing
understandnumeric3 unique values
0 missing
predominnumeric3 unique values
0 missing
physiolognumeric4 unique values
0 missing
shortlinumeric2 unique values
0 missing
danumeric4 unique values
0 missing
tobramycinnumeric4 unique values
0 missing
lethalnumeric2 unique values
0 missing
narrownumeric2 unique values
0 missing
epinephrinnumeric5 unique values
0 missing
bluntnumeric3 unique values
0 missing
idealnumeric3 unique values
0 missing
metabolnumeric8 unique values
0 missing
accessorinumeric4 unique values
0 missing
angiographnumeric3 unique values
0 missing
zealandnumeric3 unique values
0 missing
behavnumeric2 unique values
0 missing
denumeric4 unique values
0 missing
tfnumeric5 unique values
0 missing
lipopolysaccharidnumeric4 unique values
0 missing
passagnumeric3 unique values
0 missing
dnanumeric11 unique values
0 missing
guidnumeric2 unique values
0 missing
contextnumeric3 unique values
0 missing
vesiclnumeric2 unique values
0 missing
acetnumeric4 unique values
0 missing
attainnumeric2 unique values
0 missing
stainnumeric6 unique values
0 missing
phosphorunumeric4 unique values
0 missing
dinumeric5 unique values
0 missing
angioplastinumeric4 unique values
0 missing
colonnumeric5 unique values
0 missing
amplitudnumeric3 unique values
0 missing
entirnumeric2 unique values
0 missing
tcrnumeric8 unique values
0 missing
adrenoceptornumeric3 unique values
0 missing
consumnumeric4 unique values
0 missing
bovinnumeric7 unique values
0 missing
lengthnumeric5 unique values
0 missing
medianumeric5 unique values
0 missing
sulfatnumeric5 unique values
0 missing
hydrophobnumeric4 unique values
0 missing
thnumeric3 unique values
0 missing
technicnumeric2 unique values
0 missing
regenernumeric3 unique values
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dietarinumeric4 unique values
0 missing
exhibitnumeric4 unique values
0 missing
narenumeric3 unique values
0 missing
feasiblnumeric2 unique values
0 missing
singlenumeric5 unique values
0 missing
limbnumeric5 unique values
0 missing
tendencnumeric3 unique values
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histologinumeric3 unique values
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dlnumeric7 unique values
0 missing
tinumeric4 unique values
0 missing
classicnumeric2 unique values
0 missing
painnumeric4 unique values
0 missing
ristocetinnumeric4 unique values
0 missing
ureanumeric7 unique values
0 missing
organelnumeric3 unique values
0 missing
outcomnumeric4 unique values
0 missing
preservnumeric3 unique values
0 missing
carcinomanumeric5 unique values
0 missing
mannernumeric4 unique values
0 missing
febrilnumeric2 unique values
0 missing
ambulatorinumeric4 unique values
0 missing
eliminnumeric4 unique values
0 missing
classifnumeric3 unique values
0 missing
prevalnumeric4 unique values
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increasnumeric13 unique values
0 missing
communnumeric5 unique values
0 missing
overalnumeric4 unique values
0 missing
detectnumeric6 unique values
0 missing
helpnumeric3 unique values
0 missing
phosphatidnumeric4 unique values
0 missing
medicnumeric5 unique values
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refernumeric4 unique values
0 missing
ligatnumeric4 unique values
0 missing
decembnumeric2 unique values
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postopnumeric6 unique values
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pairnumeric5 unique values
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dialysnumeric5 unique values
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tubenumeric4 unique values
0 missing
agonistnumeric7 unique values
0 missing
irradinumeric5 unique values
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provenumeric2 unique values
0 missing
oilnumeric4 unique values
0 missing
opportunnumeric2 unique values
0 missing
predominantlinumeric3 unique values
0 missing
wavenumeric4 unique values
0 missing
centrenumeric3 unique values
0 missing
lactamasnumeric4 unique values
0 missing
lessernumeric2 unique values
0 missing
supplemnumeric3 unique values
0 missing
sourcenumeric4 unique values
0 missing
mhcnumeric5 unique values
0 missing
participnumeric3 unique values
0 missing
cancernumeric5 unique values
0 missing
neurotoxnumeric3 unique values
0 missing
embryonumeric3 unique values
0 missing
preincubnumeric4 unique values
0 missing
drnumeric3 unique values
0 missing
deltanumeric7 unique values
0 missing
hplcnumeric3 unique values
0 missing
biosynthesinumeric3 unique values
0 missing
spenumeric3 unique values
0 missing
supernatnumeric4 unique values
0 missing
overloadnumeric4 unique values
0 missing
stimulatorinumeric5 unique values
0 missing
reviewnumeric3 unique values
0 missing
equilibriumnumeric3 unique values
0 missing
littlenumeric3 unique values
0 missing
phosphatidylnumeric3 unique values
0 missing
fewernumeric2 unique values
0 missing
furanumeric2 unique values
0 missing
absencnumeric4 unique values
0 missing
indirectnumeric3 unique values
0 missing
bluenumeric4 unique values
0 missing
malignnumeric4 unique values
0 missing
typnumeric2 unique values
0 missing
jejunumnumeric3 unique values
0 missing
freshnumeric3 unique values
0 missing
evidnumeric4 unique values
0 missing
exceednumeric3 unique values
0 missing
hereinnumeric2 unique values
0 missing
incremnumeric3 unique values
0 missing
possiblnumeric3 unique values
0 missing
nonhydrolyznumeric2 unique values
0 missing
sharenumeric2 unique values
0 missing
finalnumeric3 unique values
0 missing
uremnumeric10 unique values
0 missing
prothrombotnumeric3 unique values
0 missing
treatenumeric8 unique values
0 missing
closurnumeric3 unique values
0 missing
linenumeric7 unique values
0 missing
routenumeric2 unique values
0 missing
extractnumeric5 unique values
0 missing
dimensnumeric3 unique values
0 missing
transurethrnumeric3 unique values
0 missing
permitnumeric2 unique values
0 missing
hemorrhagnumeric6 unique values
0 missing
dialyznumeric3 unique values
0 missing
stablenumeric4 unique values
0 missing
surgerinumeric7 unique values
0 missing
deathnumeric5 unique values
0 missing
gdpnumeric4 unique values
0 missing
intracraninumeric3 unique values
0 missing
cortisolnumeric5 unique values
0 missing
ampnumeric6 unique values
0 missing
competitnumeric2 unique values
0 missing
subcutannumeric5 unique values
0 missing
permeabilnumeric4 unique values
0 missing
foldnumeric6 unique values
0 missing
denudnumeric3 unique values
0 missing
unsuccessnumeric2 unique values
0 missing
photoreceptornumeric4 unique values
0 missing
possessnumeric3 unique values
0 missing
mentalnumeric5 unique values
0 missing
inoculumnumeric2 unique values
0 missing
tomographnumeric4 unique values
0 missing
establishnumeric3 unique values
0 missing
ionnumeric5 unique values
0 missing
usnumeric5 unique values
0 missing
ventilnumeric3 unique values
0 missing
exertnumeric2 unique values
0 missing
approximnumeric3 unique values
0 missing
embryonnumeric4 unique values
0 missing
transmitnumeric3 unique values
0 missing
undergonumeric4 unique values
0 missing
aorticnumeric6 unique values
0 missing
evolvnumeric2 unique values
0 missing
strainnumeric9 unique values
0 missing
rendernumeric2 unique values
0 missing
lutealnumeric3 unique values
0 missing
filamnumeric5 unique values
0 missing
absentnumeric3 unique values
0 missing
issuenumeric2 unique values
0 missing
dognumeric8 unique values
0 missing
stablinumeric2 unique values
0 missing
sitenumeric8 unique values
0 missing
scatternumeric2 unique values
0 missing
oxacillinnumeric5 unique values
0 missing
minutnumeric7 unique values
0 missing
phorbolnumeric8 unique values
0 missing
calcifnumeric3 unique values
0 missing
spinalnumeric5 unique values
0 missing
amnesnumeric3 unique values
0 missing
recruitnumeric4 unique values
0 missing
naturnumeric3 unique values
0 missing
techniqunumeric5 unique values
0 missing
notablnumeric2 unique values
0 missing
libitumnumeric3 unique values
0 missing
earliestnumeric3 unique values
0 missing
microvasculaturnumeric3 unique values
0 missing
linknumeric7 unique values
0 missing
hemodialysinumeric6 unique values
0 missing
reproducnumeric3 unique values
0 missing
clearnumeric2 unique values
0 missing
vanumeric4 unique values
0 missing
resultnumeric6 unique values
0 missing
surprisinglinumeric2 unique values
0 missing
conspicunumeric2 unique values
0 missing
phosphoinositidnumeric5 unique values
0 missing
epitheliumnumeric4 unique values
0 missing
glassnumeric2 unique values
0 missing
fasternumeric2 unique values
0 missing
etiolognumeric3 unique values
0 missing
explornumeric2 unique values
0 missing
mucosnumeric3 unique values
0 missing
prelabelnumeric2 unique values
0 missing
thirdnumeric3 unique values
0 missing
acetylcholinnumeric3 unique values
0 missing
thresholdnumeric3 unique values
0 missing
dorsalnumeric3 unique values
0 missing
somatostatinnumeric3 unique values
0 missing
believnumeric2 unique values
0 missing
polyacrylamidnumeric3 unique values
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suspectnumeric3 unique values
0 missing
cellularnumeric4 unique values
0 missing
respondnumeric6 unique values
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disruptnumeric6 unique values
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ecnumeric7 unique values
0 missing
carbohydrnumeric3 unique values
0 missing
newlinumeric2 unique values
0 missing
perfornumeric4 unique values
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dosnumeric3 unique values
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scavengnumeric2 unique values
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micnumeric5 unique values
0 missing
uninfectnumeric3 unique values
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exposnumeric6 unique values
0 missing
alveolarnumeric5 unique values
0 missing
spectroscopinumeric4 unique values
0 missing
experinumeric6 unique values
0 missing
primarilinumeric2 unique values
0 missing
yagnumeric3 unique values
0 missing
potentinumeric5 unique values
0 missing
summarnumeric2 unique values
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fibrinolysinumeric2 unique values
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intoxnumeric3 unique values
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causalnumeric2 unique values
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cascadnumeric4 unique values
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sixthnumeric2 unique values
0 missing
organnumeric6 unique values
0 missing
bacteremnumeric4 unique values
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percentnumeric6 unique values
0 missing
cleavnumeric3 unique values
0 missing
beatenumeric2 unique values
0 missing
immunoassainumeric2 unique values
0 missing
purulnumeric2 unique values
0 missing
tendnumeric2 unique values
0 missing
retentnumeric5 unique values
0 missing
midnumeric4 unique values
0 missing
nosocominumeric6 unique values
0 missing
floranumeric3 unique values
0 missing
increasinglinumeric3 unique values
0 missing
anteriornumeric4 unique values
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zymosannumeric4 unique values
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bradykininnumeric4 unique values
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waternumeric4 unique values
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mildnumeric3 unique values
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carenumeric5 unique values
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particularlinumeric2 unique values
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covalnumeric3 unique values
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granulomatnumeric3 unique values
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greatlinumeric2 unique values
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gelnumeric5 unique values
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neurobehaviornumeric2 unique values
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responsnumeric11 unique values
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angnumeric4 unique values
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egnumeric4 unique values
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unaltnumeric3 unique values
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carboxinumeric3 unique values
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disseminnumeric3 unique values
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deletionnumeric3 unique values
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osteoidnumeric2 unique values
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isocalornumeric2 unique values
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incompletnumeric2 unique values
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infrequnumeric2 unique values
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urinarinumeric4 unique values
0 missing
hlanumeric2 unique values
0 missing
xanthinnumeric3 unique values
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voltagnumeric4 unique values
0 missing
monomnumeric4 unique values
0 missing
bactericidnumeric4 unique values
0 missing
crystalnumeric4 unique values
0 missing
belongnumeric3 unique values
0 missing
striatumnumeric3 unique values
0 missing
adenylnumeric6 unique values
0 missing
sequentinumeric3 unique values
0 missing
elevennumeric2 unique values
0 missing
isotopnumeric3 unique values
0 missing
futurnumeric2 unique values
0 missing
purenumeric2 unique values
0 missing
thrombolysinumeric3 unique values
0 missing
multiplnumeric5 unique values
0 missing
tetradecanoylnumeric3 unique values
0 missing
ubiquitnumeric2 unique values
0 missing
proteolysinumeric4 unique values
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clarifinumeric2 unique values
0 missing
rejectnumeric4 unique values
0 missing
genomnumeric2 unique values
0 missing
proteinnumeric13 unique values
0 missing
garnetnumeric3 unique values
0 missing
consumptnumeric5 unique values
0 missing
instillnumeric3 unique values
0 missing
exnumeric3 unique values
0 missing
revisnumeric2 unique values
0 missing
irreversnumeric4 unique values
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surfacnumeric9 unique values
0 missing
vasopressinnumeric5 unique values
0 missing
hyperplasianumeric2 unique values
0 missing
Show first 100 features

107 properties

NumberOfInstances
913
Number of instances (rows) of the dataset.
NumberOfFeatures
3101
Number of attributes (columns) of the dataset.
NumberOfClasses
10
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
3100
Number of numeric attributes.
NumberOfSymbolicFeatures
1
Number of nominal attributes.
Quartile1SkewnessOfNumericAtts
10.26
First quartile of skewness among attributes of the numeric type.
REPTreeDepth1Kappa
0.54
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
CfsSubsetEval_kNN1NAUC
0.9
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
StdvNominalAttDistinctValues
0
Standard deviation of the number of distinct values among attributes of the nominal type.
J48.001.ErrRate
0.31
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
MeanNominalAttDistinctValues
10
Average number of distinct values among the attributes of the nominal type.
Quartile1StdDevOfNumericAtts
0.1
First quartile of standard deviation of attributes of the numeric type.
REPTreeDepth2AUC
0.86
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
CfsSubsetEval_kNN1NErrRate
0.26
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
kNN1NAUC
0.54
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
J48.001.Kappa
0.65
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
MeanSkewnessOfNumericAtts
14.43
Mean skewness among attributes of the numeric type.
Quartile2AttributeEntropy
Second quartile (Median) of entropy among attributes.
REPTreeDepth2ErrRate
0.4
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
CfsSubsetEval_kNN1NKappa
0.7
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
kNN1NErrRate
0.8
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
MajorityClassPercentage
17.2
Percentage of instances belonging to the most frequent class.
MeanStdDevOfNumericAtts
0.23
Mean standard deviation of attributes of the numeric type.
Quartile2KurtosisOfNumericAtts
224.49
Second quartile (Median) of kurtosis among attributes of the numeric type.
REPTreeDepth2Kappa
0.54
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
ClassEntropy
3.21
Entropy of the target attribute values.
kNN1NKappa
0.08
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
MajorityClassSize
157
Number of instances belonging to the most frequent class.
MinAttributeEntropy
Minimal entropy among attributes.
Quartile2MeansOfNumericAtts
0.01
Second quartile (Median) of means among attributes of the numeric type.
REPTreeDepth3AUC
0.86
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
DecisionStumpAUC
0.6
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
MaxAttributeEntropy
Maximum entropy among attributes.
MinKurtosisOfNumericAtts
2.49
Minimum kurtosis among attributes of the numeric type.
Quartile2MutualInformation
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
REPTreeDepth3ErrRate
0.4
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
DecisionStumpErrRate
0.73
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
MaxKurtosisOfNumericAtts
898.58
Maximum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
0
Minimum of means among attributes of the numeric type.
Quartile2SkewnessOfNumericAtts
14.47
Second quartile (Median) of skewness among attributes of the numeric type.
REPTreeDepth3Kappa
0.54
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
DecisionStumpKappa
0.13
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
MaxMeansOfNumericAtts
2.19
Maximum of means among attributes of the numeric type.
MinMutualInformation
Minimal mutual information between the nominal attributes and the target attribute.
PercentageOfBinaryFeatures
0
Percentage of binary attributes.
Quartile2StdDevOfNumericAtts
0.17
Second quartile (Median) of standard deviation of attributes of the numeric type.
RandomTreeDepth1AUC
0.64
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
Dimensionality
3.4
Number of attributes divided by the number of instances.
MaxMutualInformation
Maximum mutual information between the nominal attributes and the target attribute.
MinNominalAttDistinctValues
10
The minimal number of distinct values among attributes of the nominal type.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
Quartile3AttributeEntropy
Third quartile of entropy among attributes.
RandomTreeDepth1ErrRate
0.64
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
EquivalentNumberOfAtts
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
MaxNominalAttDistinctValues
10
The maximum number of distinct values among attributes of the nominal type.
MinSkewnessOfNumericAtts
1.5
Minimum skewness among attributes of the numeric type.
PercentageOfMissingValues
0
Percentage of missing values.
Quartile3KurtosisOfNumericAtts
351.23
Third quartile of kurtosis among attributes of the numeric type.
AutoCorrelation
0.23
Average class difference between consecutive instances.
RandomTreeDepth1Kappa
0.28
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
J48.00001.AUC
0.85
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
MaxSkewnessOfNumericAtts
29.87
Maximum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
0.06
Minimum standard deviation of attributes of the numeric type.
PercentageOfNumericFeatures
99.97
Percentage of numeric attributes.
Quartile3MeansOfNumericAtts
0.03
Third quartile of means among attributes of the numeric type.
CfsSubsetEval_DecisionStumpAUC
0.9
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
RandomTreeDepth2AUC
0.64
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
J48.00001.ErrRate
0.31
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
MaxStdDevOfNumericAtts
4.95
Maximum standard deviation of attributes of the numeric type.
MinorityClassPercentage
5.81
Percentage of instances belonging to the least frequent class.
PercentageOfSymbolicFeatures
0.03
Percentage of nominal attributes.
Quartile3MutualInformation
Third quartile of mutual information between the nominal attributes and the target attribute.
CfsSubsetEval_DecisionStumpErrRate
0.26
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
RandomTreeDepth2ErrRate
0.64
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
J48.00001.Kappa
0.65
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
MeanAttributeEntropy
Average entropy of the attributes.
MinorityClassSize
53
Number of instances belonging to the least frequent class.
Quartile1AttributeEntropy
First quartile of entropy among attributes.
Quartile3SkewnessOfNumericAtts
17.89
Third quartile of skewness among attributes of the numeric type.
CfsSubsetEval_DecisionStumpKappa
0.7
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
RandomTreeDepth2Kappa
0.28
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
J48.0001.AUC
0.85
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
MeanKurtosisOfNumericAtts
260.15
Mean kurtosis among attributes of the numeric type.
NaiveBayesAUC
0.91
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
Quartile1KurtosisOfNumericAtts
117.1
First quartile of kurtosis among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
0.28
Third quartile of standard deviation of attributes of the numeric type.
CfsSubsetEval_NaiveBayesAUC
0.9
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
RandomTreeDepth3AUC
0.64
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
J48.0001.ErrRate
0.31
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
MeanMeansOfNumericAtts
0.03
Mean of means among attributes of the numeric type.
NaiveBayesErrRate
0.31
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
Quartile1MeansOfNumericAtts
0.01
First quartile of means among attributes of the numeric type.
REPTreeDepth1AUC
0.86
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
CfsSubsetEval_NaiveBayesErrRate
0.26
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
RandomTreeDepth3ErrRate
0.64
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
J48.0001.Kappa
0.65
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
MeanMutualInformation
Average mutual information between the nominal attributes and the target attribute.
NaiveBayesKappa
0.65
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
Quartile1MutualInformation
First quartile of mutual information between the nominal attributes and the target attribute.
REPTreeDepth1ErrRate
0.4
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
CfsSubsetEval_NaiveBayesKappa
0.7
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
RandomTreeDepth3Kappa
0.28
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
J48.001.AUC
0.85
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
MeanNoiseToSignalRatio
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
NumberOfBinaryFeatures
0
Number of binary attributes.
Show all 107 properties

62 tasks

Supervised Classification on oh15.wc
243 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: CLASS_LABEL
Supervised Classification on oh15.wc
94 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: CLASS_LABEL
Supervised Regression on oh15.wc
0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: mean_absolute_error - target_feature: class
Supervised Regression on oh15.wc
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: mean_absolute_error - target_feature: class
Supervised Regression on oh15.wc
0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
Supervised Regression on oh15.wc
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
Supervised Regression on oh15.wc
0 runs - estimation_procedure: Custom 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
Supervised Regression on oh15.wc
0 runs - estimation_procedure: Test on Training Data - evaluation_measure: predictive_accuracy - target_feature: class
Supervised Regression on oh15.wc
0 runs - estimation_procedure: 5 times 2-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
Learning Curve on oh15.wc
40 runs - estimation_procedure: 10-fold Learning Curve - target_feature: CLASS_LABEL
Supervised Data Stream Classification on oh15.wc
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: CLASS_LABEL
Clustering on oh15.wc
0 runs - estimation_procedure: 50 times Clustering
Clustering on oh15.wc
0 runs - estimation_procedure: 50 times Clustering
Clustering on oh15.wc
0 runs - estimation_procedure: 50 times Clustering
Clustering on oh15.wc
0 runs - estimation_procedure: 50 times Clustering
Clustering on oh15.wc
0 runs - estimation_procedure: 50 times Clustering
Clustering on oh15.wc
0 runs
Clustering on oh15.wc
0 runs - estimation_procedure: 50 times Clustering
Clustering on oh15.wc
0 runs - estimation_procedure: 50 times Clustering
Clustering on oh15.wc
0 runs - estimation_procedure: 50 times Clustering
Clustering on oh15.wc
0 runs - estimation_procedure: 50 times Clustering
Clustering on oh15.wc
0 runs - estimation_procedure: 50 times Clustering
Subgroup Discovery on oh15.wc
0 runs - target_feature: CLASS_LABEL
Subgroup Discovery on oh15.wc
0 runs - target_feature: CLASS_LABEL
Subgroup Discovery on oh15.wc
0 runs - target_feature: CLASS_LABEL
Subgroup Discovery on oh15.wc
0 runs - target_feature: CLASS_LABEL
Subgroup Discovery on oh15.wc
0 runs - target_feature: CLASS_LABEL
Subgroup Discovery on oh15.wc
0 runs - target_feature: CLASS_LABEL
Subgroup Discovery on oh15.wc
0 runs - target_feature: CLASS_LABEL
Subgroup Discovery on oh15.wc
0 runs - target_feature: CLASS_LABEL
Subgroup Discovery on oh15.wc
0 runs - target_feature: CLASS_LABEL
Subgroup Discovery on oh15.wc
0 runs - target_feature: CLASS_LABEL
Subgroup Discovery on oh15.wc
0 runs - target_feature: CLASS_LABEL
Subgroup Discovery on oh15.wc
0 runs - target_feature: CLASS_LABEL
Subgroup Discovery on oh15.wc
0 runs - target_feature: CLASS_LABEL
Subgroup Discovery on oh15.wc
0 runs - target_feature: CLASS_LABEL
Subgroup Discovery on oh15.wc
0 runs - target_feature: CLASS_LABEL
Subgroup Discovery on oh15.wc
0 runs - target_feature: CLASS_LABEL
Subgroup Discovery on oh15.wc
0 runs - target_feature: CLASS_LABEL
Subgroup Discovery on oh15.wc
0 runs - target_feature: CLASS_LABEL
Subgroup Discovery on oh15.wc
0 runs - target_feature: CLASS_LABEL
Subgroup Discovery on oh15.wc
0 runs - target_feature: CLASS_LABEL
Subgroup Discovery on oh15.wc
0 runs - target_feature: CLASS_LABEL
Subgroup Discovery on oh15.wc
0 runs - target_feature: CLASS_LABEL
Subgroup Discovery on oh15.wc
0 runs - target_feature: CLASS_LABEL
Subgroup Discovery on oh15.wc
0 runs - target_feature: CLASS_LABEL
Subgroup Discovery on oh15.wc
0 runs - target_feature: CLASS_LABEL
Subgroup Discovery on oh15.wc
0 runs - target_feature: CLASS_LABEL
Subgroup Discovery on oh15.wc
0 runs - target_feature: CLASS_LABEL
Subgroup Discovery on oh15.wc
0 runs - target_feature: CLASS_LABEL
Subgroup Discovery on oh15.wc
0 runs - target_feature: CLASS_LABEL
Subgroup Discovery on oh15.wc
0 runs - target_feature: CLASS_LABEL
Subgroup Discovery on oh15.wc
0 runs - target_feature: CLASS_LABEL
Subgroup Discovery on oh15.wc
0 runs - target_feature: CLASS_LABEL
Subgroup Discovery on oh15.wc
0 runs - target_feature: CLASS_LABEL
Subgroup Discovery on oh15.wc
0 runs - target_feature: CLASS_LABEL
Subgroup Discovery on oh15.wc
0 runs - target_feature: CLASS_LABEL
Subgroup Discovery on oh15.wc
0 runs - target_feature: CLASS_LABEL
Subgroup Discovery on oh15.wc
0 runs - target_feature: CLASS_LABEL
Subgroup Discovery on oh15.wc
0 runs - target_feature: CLASS_LABEL
Subgroup Discovery on oh15.wc
0 runs - target_feature: CLASS_LABEL
Subgroup Discovery on oh15.wc
0 runs - target_feature: CLASS_LABEL
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