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oh10.wc

active Sparse_ARFF Publicly available Visibility: public Uploaded 28-09-2014 by Joaquin Vanschoren
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3239 features

CLASS_LABEL (target)	nominal	10 unique values 0 missing
sudden	numeric	3 unique values 0 missing
breast	numeric	5 unique values 0 missing
deviat	numeric	3 unique values 0 missing
iv	numeric	5 unique values 0 missing
research	numeric	5 unique values 0 missing
denerv	numeric	4 unique values 0 missing
occup	numeric	3 unique values 0 missing
discrep	numeric	2 unique values 0 missing
emphas	numeric	2 unique values 0 missing
ward	numeric	3 unique values 0 missing
systemat	numeric	2 unique values 0 missing
recognis	numeric	3 unique values 0 missing
occlus	numeric	4 unique values 0 missing
gland	numeric	4 unique values 0 missing
fructos	numeric	4 unique values 0 missing
alcohol	numeric	11 unique values 0 missing
provinc	numeric	3 unique values 0 missing
effector	numeric	3 unique values 0 missing
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occur	numeric	5 unique values 0 missing
reactiv	numeric	5 unique values 0 missing
misunderstand	numeric	2 unique values 0 missing
azt	numeric	3 unique values 0 missing
challeng	numeric	3 unique values 0 missing
enter	numeric	4 unique values 0 missing
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signific	numeric	6 unique values 0 missing
precis	numeric	3 unique values 0 missing
potassium	numeric	6 unique values 0 missing
compound	numeric	3 unique values 0 missing
strictli	numeric	2 unique values 0 missing
count	numeric	8 unique values 0 missing
lobe	numeric	3 unique values 0 missing
epidermi	numeric	3 unique values 0 missing
postprandi	numeric	7 unique values 0 missing
creatinin	numeric	6 unique values 0 missing
recogn	numeric	2 unique values 0 missing
transmembran	numeric	2 unique values 0 missing
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penetr	numeric	7 unique values 0 missing
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charge	numeric	5 unique values 0 missing
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week	numeric	7 unique values 0 missing
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thermal	numeric	3 unique values 0 missing
glucocorticoid	numeric	3 unique values 0 missing
cultur	numeric	6 unique values 0 missing
relat	numeric	8 unique values 0 missing
trial	numeric	6 unique values 0 missing
hold	numeric	2 unique values 0 missing
autoimmun	numeric	3 unique values 0 missing
devic	numeric	3 unique values 0 missing
bulk	numeric	2 unique values 0 missing
melanoma	numeric	2 unique values 0 missing
cellular	numeric	4 unique values 0 missing
intermedi	numeric	4 unique values 0 missing
arrest	numeric	6 unique values 0 missing
force	numeric	4 unique values 0 missing
anatom	numeric	3 unique values 0 missing
malnutrit	numeric	4 unique values 0 missing
vision	numeric	2 unique values 0 missing
fear	numeric	2 unique values 0 missing
hole	numeric	4 unique values 0 missing
probabl	numeric	4 unique values 0 missing
press	numeric	2 unique values 0 missing
malaria	numeric	4 unique values 0 missing
cleavag	numeric	3 unique values 0 missing
increasingli	numeric	2 unique values 0 missing
develop	numeric	4 unique values 0 missing
assai	numeric	5 unique values 0 missing
enzym	numeric	6 unique values 0 missing
collagen	numeric	5 unique values 0 missing
women	numeric	8 unique values 0 missing
miner	numeric	3 unique values 0 missing
contrari	numeric	2 unique values 0 missing
adhesion	numeric	3 unique values 0 missing
total	numeric	8 unique values 0 missing
dry	numeric	3 unique values 0 missing
absorb	numeric	3 unique values 0 missing
insult	numeric	2 unique values 0 missing
isotop	numeric	2 unique values 0 missing
ahead	numeric	2 unique values 0 missing
nd	numeric	4 unique values 0 missing
lipas	numeric	4 unique values 0 missing
liv	numeric	4 unique values 0 missing
origin	numeric	5 unique values 0 missing
relax	numeric	5 unique values 0 missing
ultrasonographi	numeric	4 unique values 0 missing
distress	numeric	2 unique values 0 missing
postul	numeric	2 unique values 0 missing
devis	numeric	2 unique values 0 missing
elut	numeric	3 unique values 0 missing
fsh	numeric	4 unique values 0 missing
induct	numeric	4 unique values 0 missing
parasit	numeric	4 unique values 0 missing
ng	numeric	6 unique values 0 missing
purif	numeric	2 unique values 0 missing
databas	numeric	4 unique values 0 missing
judg	numeric	2 unique values 0 missing
twin	numeric	5 unique values 0 missing
chorioretin	numeric	3 unique values 0 missing
importantli	numeric	2 unique values 0 missing
postur	numeric	3 unique values 0 missing
satisfact	numeric	3 unique values 0 missing
simple	numeric	3 unique values 0 missing
dilut	numeric	3 unique values 0 missing
abund	numeric	3 unique values 0 missing
presum	numeric	2 unique values 0 missing
modifi	numeric	3 unique values 0 missing
account	numeric	4 unique values 0 missing
perspect	numeric	3 unique values 0 missing
night	numeric	5 unique values 0 missing
vigor	numeric	2 unique values 0 missing
couple	numeric	5 unique values 0 missing
create	numeric	3 unique values 0 missing
chi	numeric	3 unique values 0 missing
extravascular	numeric	4 unique values 0 missing
dose	numeric	7 unique values 0 missing
york	numeric	2 unique values 0 missing
fruit	numeric	4 unique values 0 missing
lyso	numeric	3 unique values 0 missing
nm	numeric	4 unique values 0 missing
variou	numeric	4 unique values 0 missing
alzheim	numeric	6 unique values 0 missing
intracellular	numeric	4 unique values 0 missing
armi	numeric	3 unique values 0 missing
expect	numeric	6 unique values 0 missing
smok	numeric	9 unique values 0 missing
abstract	numeric	2 unique values 0 missing
physiologi	numeric	3 unique values 0 missing
wedge	numeric	3 unique values 0 missing
azoospermia	numeric	3 unique values 0 missing
exist	numeric	3 unique values 0 missing
diabet	numeric	8 unique values 0 missing
nt	numeric	4 unique values 0 missing
updat	numeric	3 unique values 0 missing
clone	numeric	3 unique values 0 missing
pressur	numeric	13 unique values 0 missing
inadequaci	numeric	2 unique values 0 missing
molecul	numeric	3 unique values 0 missing
impair	numeric	5 unique values 0 missing
cho	numeric	4 unique values 0 missing
target	numeric	4 unique values 0 missing
vasodil	numeric	5 unique values 0 missing
usual	numeric	3 unique values 0 missing
drinker	numeric	3 unique values 0 missing
dystocia	numeric	3 unique values 0 missing
ny	numeric	2 unique values 0 missing
mesenter	numeric	6 unique values 0 missing
recipi	numeric	6 unique values 0 missing
antagonist	numeric	7 unique values 0 missing
photograph	numeric	3 unique values 0 missing
regard	numeric	3 unique values 0 missing
bilater	numeric	3 unique values 0 missing
benefit	numeric	5 unique values 0 missing
analys	numeric	4 unique values 0 missing
ischem	numeric	5 unique values 0 missing
blood	numeric	11 unique values 0 missing
sixfold	numeric	2 unique values 0 missing
region	numeric	6 unique values 0 missing
transport	numeric	5 unique values 0 missing
itali	numeric	4 unique values 0 missing
fall	numeric	7 unique values 0 missing
nutrient	numeric	6 unique values 0 missing
suppress	numeric	7 unique values 0 missing
paf	numeric	6 unique values 0 missing
referr	numeric	3 unique values 0 missing
hematopoiet	numeric	4 unique values 0 missing
analyt	numeric	4 unique values 0 missing
slowli	numeric	2 unique values 0 missing
uterin	numeric	4 unique values 0 missing
undetect	numeric	2 unique values 0 missing
disclos	numeric	2 unique values 0 missing
complem	numeric	3 unique values 0 missing
vitamin	numeric	9 unique values 0 missing
expand	numeric	4 unique values 0 missing
calori	numeric	7 unique values 0 missing
biopsi	numeric	5 unique values 0 missing
pai	numeric	4 unique values 0 missing
home	numeric	6 unique values 0 missing
healthi	numeric	5 unique values 0 missing
sub	numeric	3 unique values 0 missing
osmolar	numeric	2 unique values 0 missing
readili	numeric	3 unique values 0 missing
replic	numeric	2 unique values 0 missing
febril	numeric	3 unique values 0 missing
recombin	numeric	6 unique values 0 missing
methodologi	numeric	2 unique values 0 missing
vital	numeric	2 unique values 0 missing
concentr	numeric	10 unique values 0 missing
multidisciplinari	numeric	2 unique values 0 missing
reliabl	numeric	4 unique values 0 missing
cyclic	numeric	3 unique values 0 missing
amnion	numeric	3 unique values 0 missing
enroll	numeric	3 unique values 0 missing
context	numeric	2 unique values 0 missing
describ	numeric	4 unique values 0 missing
disciplin	numeric	2 unique values 0 missing
refer	numeric	4 unique values 0 missing
item	numeric	5 unique values 0 missing
season	numeric	2 unique values 0 missing
fertil	numeric	8 unique values 0 missing
twofold	numeric	2 unique values 0 missing
suscept	numeric	3 unique values 0 missing
autolog	numeric	4 unique values 0 missing
coincid	numeric	2 unique values 0 missing
amniot	numeric	4 unique values 0 missing
analyz	numeric	3 unique values 0 missing
overal	numeric	4 unique values 0 missing
paediatr	numeric	3 unique values 0 missing
serotonin	numeric	3 unique values 0 missing
predominantli	numeric	3 unique values 0 missing
quickli	numeric	2 unique values 0 missing
capac	numeric	6 unique values 0 missing
expans	numeric	4 unique values 0 missing
mitochondri	numeric	4 unique values 0 missing
maneuv	numeric	3 unique values 0 missing
intraop	numeric	4 unique values 0 missing
glomerular	numeric	7 unique values 0 missing
prenat	numeric	5 unique values 0 missing
conduct	numeric	3 unique values 0 missing
typ	numeric	4 unique values 0 missing
remnant	numeric	4 unique values 0 missing
hybrid	numeric	4 unique values 0 missing
preincub	numeric	4 unique values 0 missing
od	numeric	4 unique values 0 missing
weakli	numeric	2 unique values 0 missing
postabsorpt	numeric	3 unique values 0 missing
return	numeric	4 unique values 0 missing
fortifi	numeric	3 unique values 0 missing
pap	numeric	4 unique values 0 missing
materi	numeric	4 unique values 0 missing
pentobarbit	numeric	2 unique values 0 missing
suboptim	numeric	2 unique values 0 missing
surgeri	numeric	6 unique values 0 missing
transfus	numeric	3 unique values 0 missing
leukotrien	numeric	6 unique values 0 missing
extract	numeric	4 unique values 0 missing
complet	numeric	4 unique values 0 missing
correspond	numeric	3 unique values 0 missing
north	numeric	3 unique values 0 missing
repres	numeric	3 unique values 0 missing
thin	numeric	2 unique values 0 missing
par	numeric	3 unique values 0 missing
cirrhosi	numeric	4 unique values 0 missing
kinet	numeric	3 unique values 0 missing
sum	numeric	2 unique values 0 missing
belief	numeric	2 unique values 0 missing
semen	numeric	8 unique values 0 missing
migrat	numeric	2 unique values 0 missing
establish	numeric	4 unique values 0 missing
oh	numeric	4 unique values 0 missing
habit	numeric	3 unique values 0 missing
differ	numeric	5 unique values 0 missing
chromosom	numeric	6 unique values 0 missing
matrix	numeric	3 unique values 0 missing
chronic	numeric	7 unique values 0 missing
pelvic	numeric	2 unique values 0 missing
sympathet	numeric	5 unique values 0 missing
resolv	numeric	2 unique values 0 missing
photoreceptor	numeric	3 unique values 0 missing
fluorescein	numeric	3 unique values 0 missing
handl	numeric	3 unique values 0 missing
reproduc	numeric	2 unique values 0 missing
complex	numeric	3 unique values 0 missing
anti	numeric	6 unique values 0 missing
pictur	numeric	2 unique values 0 missing
metabolit	numeric	7 unique values 0 missing
hypertens	numeric	9 unique values 0 missing
percentil	numeric	3 unique values 0 missing
matern	numeric	8 unique values 0 missing
hard	numeric	2 unique values 0 missing
consciou	numeric	3 unique values 0 missing
epithelium	numeric	3 unique values 0 missing
onto	numeric	2 unique values 0 missing
angiographi	numeric	3 unique values 0 missing
disadvantag	numeric	2 unique values 0 missing
parent	numeric	7 unique values 0 missing
focu	numeric	5 unique values 0 missing
magnitud	numeric	3 unique values 0 missing
postmenopaus	numeric	3 unique values 0 missing
oxidas	numeric	4 unique values 0 missing
ingest	numeric	8 unique values 0 missing
pediatr	numeric	5 unique values 0 missing
cit	numeric	2 unique values 0 missing
transduc	numeric	2 unique values 0 missing
libitum	numeric	5 unique values 0 missing
consist	numeric	4 unique values 0 missing
illustr	numeric	2 unique values 0 missing
mucos	numeric	3 unique values 0 missing
false	numeric	4 unique values 0 missing
altern	numeric	3 unique values 0 missing
outbreak	numeric	2 unique values 0 missing
gener	numeric	6 unique values 0 missing
born	numeric	4 unique values 0 missing
contrast	numeric	5 unique values 0 missing
corticosteroid	numeric	3 unique values 0 missing
cognit	numeric	4 unique values 0 missing
consecut	numeric	3 unique values 0 missing
believ	numeric	2 unique values 0 missing
cumul	numeric	3 unique values 0 missing
rectal	numeric	2 unique values 0 missing
percent	numeric	8 unique values 0 missing
hypoglycemia	numeric	4 unique values 0 missing
breech	numeric	5 unique values 0 missing
trend	numeric	3 unique values 0 missing
explain	numeric	5 unique values 0 missing
learn	numeric	3 unique values 0 missing
instanc	numeric	2 unique values 0 missing
androgen	numeric	2 unique values 0 missing
tubul	numeric	3 unique values 0 missing
construct	numeric	2 unique values 0 missing
isocalor	numeric	3 unique values 0 missing
relationship	numeric	4 unique values 0 missing
primipar	numeric	4 unique values 0 missing
jama	numeric	2 unique values 0 missing
detriment	numeric	2 unique values 0 missing
council	numeric	2 unique values 0 missing
uncertainti	numeric	2 unique values 0 missing
genet	numeric	4 unique values 0 missing
baselin	numeric	5 unique values 0 missing
fece	numeric	3 unique values 0 missing
inactiv	numeric	3 unique values 0 missing
oocyt	numeric	7 unique values 0 missing
quantit	numeric	4 unique values 0 missing
eye	numeric	8 unique values 0 missing
cdna	numeric	3 unique values 0 missing
vitrectomi	numeric	3 unique values 0 missing
ethnic	numeric	3 unique values 0 missing
morphometr	numeric	3 unique values 0 missing
cytoplasm	numeric	5 unique values 0 missing
nuclear	numeric	5 unique values 0 missing
lipoprotein	numeric	8 unique values 0 missing
dementia	numeric	5 unique values 0 missing
birth	numeric	10 unique values 0 missing
restrict	numeric	7 unique values 0 missing
societi	numeric	4 unique values 0 missing
student	numeric	8 unique values 0 missing
starch	numeric	5 unique values 0 missing
formula	numeric	5 unique values 0 missing
offset	numeric	2 unique values 0 missing
instill	numeric	3 unique values 0 missing
pg	numeric	7 unique values 0 missing
pack	numeric	5 unique values 0 missing
parallel	numeric	2 unique values 0 missing
abil	numeric	5 unique values 0 missing
strongest	numeric	2 unique values 0 missing
ovarian	numeric	3 unique values 0 missing
light	numeric	3 unique values 0 missing
psychiatr	numeric	5 unique values 0 missing
instead	numeric	2 unique values 0 missing
heterosexu	numeric	2 unique values 0 missing
funduscop	numeric	2 unique values 0 missing
tail	numeric	3 unique values 0 missing
deoxyribonucl	numeric	3 unique values 0 missing
ph	numeric	6 unique values 0 missing
uncertain	numeric	2 unique values 0 missing
highlight	numeric	3 unique values 0 missing
barrier	numeric	5 unique values 0 missing
cross	numeric	5 unique values 0 missing
keto	numeric	6 unique values 0 missing
concurr	numeric	2 unique values 0 missing
urolog	numeric	4 unique values 0 missing
predict	numeric	6 unique values 0 missing
unexplain	numeric	4 unique values 0 missing
unnecessari	numeric	3 unique values 0 missing
curriculum	numeric	6 unique values 0 missing
infanc	numeric	3 unique values 0 missing
unless	numeric	2 unique values 0 missing
polymorph	numeric	4 unique values 0 missing
endoscop	numeric	4 unique values 0 missing
uncommon	numeric	2 unique values 0 missing
transcript	numeric	5 unique values 0 missing
friend	numeric	2 unique values 0 missing
hemodynam	numeric	6 unique values 0 missing
clearanc	numeric	6 unique values 0 missing

Show first 100 features

107 properties

NumberOfInstances

1050

Number of instances (rows) of the dataset.

NumberOfFeatures

3239

Number of attributes (columns) of the dataset.

NumberOfClasses

Number of distinct values of the target attribute (if it is nominal).

NumberOfMissingValues

Number of missing values in the dataset.

NumberOfInstancesWithMissingValues

Number of instances with at least one value missing.

NumberOfNumericFeatures

3238

Number of numeric attributes.

NumberOfSymbolicFeatures

Number of nominal attributes.

Quartile2KurtosisOfNumericAtts

258.74

Second quartile (Median) of kurtosis among attributes of the numeric type.

REPTreeDepth2Kappa

0.64

Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2

ClassEntropy

3.2

Entropy of the target attribute values.

kNN1NKappa

0.07

Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk

MajorityClassSize

165

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

0.91

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

4.85

Minimum kurtosis among attributes of the numeric type.

Quartile2MutualInformation

Second quartile (Median) of mutual information between the nominal attributes and the target attribute.

REPTreeDepth3ErrRate

0.32

Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3

DecisionStumpErrRate

0.74

Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump

MaxKurtosisOfNumericAtts

1025.83

Maximum kurtosis among attributes of the numeric type.

MinMeansOfNumericAtts

Minimum of means among attributes of the numeric type.

Quartile2SkewnessOfNumericAtts

15.73

Second quartile (Median) of skewness among attributes of the numeric type.

REPTreeDepth3Kappa

0.64

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

1.41

Maximum of means among attributes of the numeric type.

MinMutualInformation

Minimal mutual information between the nominal attributes and the target attribute.

PercentageOfBinaryFeatures

Percentage of binary attributes.

Quartile2StdDevOfNumericAtts

0.15

Second quartile (Median) of standard deviation of attributes of the numeric type.

RandomTreeDepth1AUC

0.63

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1

Dimensionality

3.08

Number of attributes divided by the number of instances.

MaxMutualInformation

Maximum mutual information between the nominal attributes and the target attribute.

MinNominalAttDistinctValues

The minimal number of distinct values among attributes of the nominal type.

PercentageOfInstancesWithMissingValues

Percentage of instances having missing values.

Quartile3AttributeEntropy

Third quartile of entropy among attributes.

RandomTreeDepth1ErrRate

0.65

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

The maximum number of distinct values among attributes of the nominal type.

MinSkewnessOfNumericAtts

1.91

Minimum skewness among attributes of the numeric type.

PercentageOfMissingValues

Percentage of missing values.

Quartile3KurtosisOfNumericAtts

407.48

Third quartile of kurtosis among attributes of the numeric type.

AutoCorrelation

0.29

Average class difference between consecutive instances.

RandomTreeDepth1Kappa

0.26

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

31.87

Maximum skewness among attributes of the numeric type.

MinStdDevOfNumericAtts

0.05

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

0.92

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

0.63

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2

J48.00001.ErrRate

0.3

Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001

MaxStdDevOfNumericAtts

2.86

Maximum standard deviation of attributes of the numeric type.

MinorityClassPercentage

4.95

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

0.28

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

0.65

Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2

J48.00001.Kappa

0.67

Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001

MeanAttributeEntropy

Average entropy of the attributes.

MinorityClassSize

Number of instances belonging to the least frequent class.

Quartile1AttributeEntropy

First quartile of entropy among attributes.

Quartile3SkewnessOfNumericAtts

19.2

Third quartile of skewness among attributes of the numeric type.

CfsSubsetEval_DecisionStumpKappa

0.69

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

0.26

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

302.56

Mean kurtosis among attributes of the numeric type.

NaiveBayesAUC

0.92

Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes

Quartile1KurtosisOfNumericAtts

128.69

First quartile of kurtosis among attributes of the numeric type.

Quartile3StdDevOfNumericAtts

0.27

Third quartile of standard deviation of attributes of the numeric type.

CfsSubsetEval_NaiveBayesAUC

0.92

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

0.63

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3

J48.0001.ErrRate

0.3

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

0.91

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1

CfsSubsetEval_NaiveBayesErrRate

0.28

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

0.65

Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3

J48.0001.Kappa

0.67

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

0.32

Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1

CfsSubsetEval_NaiveBayesKappa

0.69

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

0.26

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

Number of binary attributes.

Quartile1SkewnessOfNumericAtts

10.68

First quartile of skewness among attributes of the numeric type.

REPTreeDepth1Kappa

0.64

Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1

CfsSubsetEval_kNN1NAUC

0.92

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

Standard deviation of the number of distinct values among attributes of the nominal type.

J48.001.ErrRate

0.3

Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001

MeanNominalAttDistinctValues

Average number of distinct values among the attributes of the nominal type.

Quartile1StdDevOfNumericAtts

0.09

First quartile of standard deviation of attributes of the numeric type.

REPTreeDepth2AUC

0.91

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2

CfsSubsetEval_kNN1NErrRate

0.28

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

0.53

Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk

J48.001.Kappa

0.67

Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001

MeanSkewnessOfNumericAtts

15.54

Mean skewness among attributes of the numeric type.

Quartile2AttributeEntropy

Second quartile (Median) of entropy among attributes.

REPTreeDepth2ErrRate

0.32

Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2

CfsSubsetEval_kNN1NKappa

0.69

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

0.85

Error rate achieved by the landmarker weka.classifiers.lazy.IBk

MajorityClassPercentage

15.71

Percentage of instances belonging to the most frequent class.

MeanStdDevOfNumericAtts

0.22

Mean standard deviation of attributes of the numeric type.

Show all 107 properties

63 tasks

Supervised Classification on oh10.wc

289 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: CLASS_LABEL

Supervised Classification on oh10.wc

92 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: CLASS_LABEL

Supervised Classification on oh10.wc

0 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: CLASS_LABEL

Supervised Regression on oh10.wc

0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: mean_absolute_error - target_feature: class

Supervised Regression on oh10.wc

0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: mean_absolute_error - target_feature: class

Supervised Regression on oh10.wc

0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class

Supervised Regression on oh10.wc

0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class

Supervised Regression on oh10.wc

0 runs - estimation_procedure: Custom 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class

Supervised Regression on oh10.wc

0 runs - estimation_procedure: Test on Training Data - evaluation_measure: predictive_accuracy - target_feature: class

Supervised Regression on oh10.wc

0 runs - estimation_procedure: 5 times 2-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class

Learning Curve on oh10.wc

35 runs - estimation_procedure: 10-fold Learning Curve - target_feature: CLASS_LABEL

Supervised Data Stream Classification on oh10.wc

0 runs - estimation_procedure: Interleaved Test then Train - target_feature: CLASS_LABEL

Clustering on oh10.wc

0 runs - estimation_procedure: 50 times Clustering

Clustering on oh10.wc

0 runs - estimation_procedure: 50 times Clustering

Clustering on oh10.wc

0 runs - estimation_procedure: 50 times Clustering

Clustering on oh10.wc

0 runs - estimation_procedure: 50 times Clustering

Clustering on oh10.wc

0 runs - estimation_procedure: 50 times Clustering

Clustering on oh10.wc

0 runs

Clustering on oh10.wc

0 runs - estimation_procedure: 50 times Clustering

Clustering on oh10.wc

0 runs - estimation_procedure: 50 times Clustering

Clustering on oh10.wc

0 runs - estimation_procedure: 50 times Clustering

Clustering on oh10.wc

0 runs - estimation_procedure: 50 times Clustering

Clustering on oh10.wc

0 runs - estimation_procedure: 50 times Clustering

Subgroup Discovery on oh10.wc