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oh0.wc

active Sparse_ARFF Publicly available Visibility: public Uploaded 28-09-2014 by Joaquin Vanschoren
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3183 features

CLASS_LABEL (target)	nominal	10 unique values 0 missing
depart	numeric	5 unique values 0 missing
gout	numeric	5 unique values 0 missing
replac	numeric	10 unique values 0 missing
fraction	numeric	7 unique values 0 missing
combin	numeric	5 unique values 0 missing
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cluster	numeric	3 unique values 0 missing
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sample	numeric	5 unique values 0 missing
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o	numeric	3 unique values 0 missing
procedur	numeric	6 unique values 0 missing
adopt	numeric	2 unique values 0 missing
band	numeric	2 unique values 0 missing
plu	numeric	5 unique values 0 missing
co	numeric	3 unique values 0 missing
doubt	numeric	2 unique values 0 missing
calcium	numeric	9 unique values 0 missing
monoclon	numeric	4 unique values 0 missing
serious	numeric	3 unique values 0 missing
safe	numeric	2 unique values 0 missing
admit	numeric	5 unique values 0 missing
nutrient	numeric	3 unique values 0 missing
june	numeric	3 unique values 0 missing
discrep	numeric	3 unique values 0 missing
supraventricular	numeric	2 unique values 0 missing
conclus	numeric	2 unique values 0 missing
vector	numeric	3 unique values 0 missing
cp	numeric	3 unique values 0 missing
counsell	numeric	4 unique values 0 missing
effusion	numeric	4 unique values 0 missing
poverti	numeric	3 unique values 0 missing
degree	numeric	5 unique values 0 missing
endoscopi	numeric	3 unique values 0 missing
slower	numeric	2 unique values 0 missing
concentr	numeric	8 unique values 0 missing
vari	numeric	3 unique values 0 missing
trauma	numeric	6 unique values 0 missing
brought	numeric	2 unique values 0 missing
percentag	numeric	4 unique values 0 missing
miscellan	numeric	3 unique values 0 missing
glycosyl	numeric	3 unique values 0 missing
st	numeric	7 unique values 0 missing
specifi	numeric	2 unique values 0 missing
uncertain	numeric	2 unique values 0 missing
appropri	numeric	4 unique values 0 missing
profession	numeric	4 unique values 0 missing
anaesthet	numeric	3 unique values 0 missing
foveal	numeric	4 unique values 0 missing
depth	numeric	4 unique values 0 missing
discret	numeric	2 unique values 0 missing
angiotensin	numeric	4 unique values 0 missing
word	numeric	2 unique values 0 missing
newborn	numeric	3 unique values 0 missing
ct	numeric	2 unique values 0 missing
discov	numeric	2 unique values 0 missing
intraven	numeric	5 unique values 0 missing
polymorph	numeric	4 unique values 0 missing
classifi	numeric	2 unique values 0 missing
north	numeric	3 unique values 0 missing
method	numeric	5 unique values 0 missing
censu	numeric	2 unique values 0 missing
v	numeric	6 unique values 0 missing
reactiv	numeric	4 unique values 0 missing
cerebellum	numeric	3 unique values 0 missing
recent	numeric	3 unique values 0 missing
imposs	numeric	2 unique values 0 missing
deficit	numeric	3 unique values 0 missing
temperatur	numeric	4 unique values 0 missing
afro	numeric	3 unique values 0 missing
maker	numeric	2 unique values 0 missing
useful	numeric	2 unique values 0 missing
addition	numeric	5 unique values 0 missing
chance	numeric	2 unique values 0 missing
abnorm	numeric	4 unique values 0 missing
metabol	numeric	4 unique values 0 missing
blockad	numeric	3 unique values 0 missing
modul	numeric	5 unique values 0 missing
motil	numeric	2 unique values 0 missing
presum	numeric	3 unique values 0 missing
inc	numeric	3 unique values 0 missing
neuroretin	numeric	2 unique values 0 missing
march	numeric	2 unique values 0 missing
implant	numeric	5 unique values 0 missing
six	numeric	4 unique values 0 missing
differ	numeric	7 unique values 0 missing
feder	numeric	3 unique values 0 missing
mitochondri	numeric	3 unique values 0 missing
manag	numeric	7 unique values 0 missing
promptli	numeric	2 unique values 0 missing
unchang	numeric	3 unique values 0 missing
exclud	numeric	2 unique values 0 missing
lysi	numeric	3 unique values 0 missing
impact	numeric	4 unique values 0 missing
rican	numeric	6 unique values 0 missing
dissect	numeric	6 unique values 0 missing
cortex	numeric	5 unique values 0 missing
valve	numeric	18 unique values 0 missing
treatment	numeric	9 unique values 0 missing
fish	numeric	4 unique values 0 missing
chosen	numeric	3 unique values 0 missing
oropharyng	numeric	3 unique values 0 missing
understand	numeric	3 unique values 0 missing
stimuli	numeric	3 unique values 0 missing
hiv	numeric	8 unique values 0 missing
diabet	numeric	10 unique values 0 missing
thorac	numeric	4 unique values 0 missing
column	numeric	3 unique values 0 missing
apprais	numeric	4 unique values 0 missing
symptom	numeric	7 unique values 0 missing
gene	numeric	6 unique values 0 missing
magnitud	numeric	3 unique values 0 missing
plana	numeric	3 unique values 0 missing
return	numeric	4 unique values 0 missing
threate	numeric	2 unique values 0 missing
held	numeric	3 unique values 0 missing
eject	numeric	7 unique values 0 missing
januari	numeric	3 unique values 0 missing
excee	numeric	2 unique values 0 missing
marker	numeric	5 unique values 0 missing
subglott	numeric	4 unique values 0 missing
bring	numeric	2 unique values 0 missing
report	numeric	7 unique values 0 missing
intact	numeric	5 unique values 0 missing
trend	numeric	5 unique values 0 missing
tri	numeric	3 unique values 0 missing
possibli	numeric	3 unique values 0 missing
incident	numeric	2 unique values 0 missing
acet	numeric	3 unique values 0 missing
inhal	numeric	3 unique values 0 missing
inact	numeric	3 unique values 0 missing
hemolysi	numeric	5 unique values 0 missing
market	numeric	2 unique values 0 missing
bmj	numeric	2 unique values 0 missing
provid	numeric	4 unique values 0 missing
csf	numeric	4 unique values 0 missing
advanc	numeric	5 unique values 0 missing
outbreak	numeric	4 unique values 0 missing
plane	numeric	2 unique values 0 missing
repres	numeric	4 unique values 0 missing
ground	numeric	2 unique values 0 missing
bovin	numeric	6 unique values 0 missing
goate	numeric	3 unique values 0 missing
exclus	numeric	3 unique values 0 missing
pharmacist	numeric	4 unique values 0 missing
confront	numeric	3 unique values 0 missing
angioplasti	numeric	4 unique values 0 missing
pose	numeric	2 unique values 0 missing
hyoid	numeric	4 unique values 0 missing
blot	numeric	2 unique values 0 missing
survei	numeric	5 unique values 0 missing
chamber	numeric	4 unique values 0 missing
kidnei	numeric	4 unique values 0 missing
consum	numeric	3 unique values 0 missing
single	numeric	3 unique values 0 missing
stimulu	numeric	4 unique values 0 missing
thoma	numeric	3 unique values 0 missing
fibrosi	numeric	3 unique values 0 missing
de	numeric	3 unique values 0 missing
appoint	numeric	3 unique values 0 missing
explicitli	numeric	2 unique values 0 missing
palliat	numeric	2 unique values 0 missing
orient	numeric	3 unique values 0 missing
practic	numeric	11 unique values 0 missing
respir	numeric	2 unique values 0 missing
chromosom	numeric	4 unique values 0 missing
feasibl	numeric	2 unique values 0 missing
preserv	numeric	5 unique values 0 missing
cardiopleg	numeric	4 unique values 0 missing
suppli	numeric	3 unique values 0 missing
crisi	numeric	2 unique values 0 missing
di	numeric	5 unique values 0 missing
elimin	numeric	3 unique values 0 missing
escherichia	numeric	3 unique values 0 missing
pericard	numeric	3 unique values 0 missing
die	numeric	3 unique values 0 missing
common	numeric	5 unique values 0 missing
success	numeric	4 unique values 0 missing
transaminas	numeric	2 unique values 0 missing
outcom	numeric	6 unique values 0 missing
help	numeric	3 unique values 0 missing
introduct	numeric	2 unique values 0 missing
cation	numeric	3 unique values 0 missing
descript	numeric	3 unique values 0 missing
dl	numeric	5 unique values 0 missing
decemb	numeric	4 unique values 0 missing
magnet	numeric	3 unique values 0 missing
effect	numeric	10 unique values 0 missing
analog	numeric	6 unique values 0 missing
nuclear	numeric	4 unique values 0 missing
frequenc	numeric	4 unique values 0 missing
metabolit	numeric	6 unique values 0 missing
detect	numeric	6 unique values 0 missing
cancer	numeric	8 unique values 0 missing
predomin	numeric	2 unique values 0 missing
physiolog	numeric	3 unique values 0 missing
withhold	numeric	3 unique values 0 missing
dm	numeric	4 unique values 0 missing
centre	numeric	4 unique values 0 missing
rai	numeric	4 unique values 0 missing
pancreat	numeric	3 unique values 0 missing
sexual	numeric	6 unique values 0 missing
aggress	numeric	3 unique values 0 missing
map	numeric	6 unique values 0 missing
suction	numeric	2 unique values 0 missing
irradi	numeric	4 unique values 0 missing
advoc	numeric	2 unique values 0 missing
angiograph	numeric	4 unique values 0 missing
stain	numeric	3 unique values 0 missing
region	numeric	6 unique values 0 missing
ligat	numeric	3 unique values 0 missing
delta	numeric	4 unique values 0 missing
discuss	numeric	5 unique values 0 missing
kda	numeric	3 unique values 0 missing
cough	numeric	4 unique values 0 missing
trent	numeric	4 unique values 0 missing
worsen	numeric	3 unique values 0 missing
explain	numeric	4 unique values 0 missing
particip	numeric	3 unique values 0 missing
obscur	numeric	2 unique values 0 missing
length	numeric	3 unique values 0 missing
media	numeric	4 unique values 0 missing
phosphoru	numeric	2 unique values 0 missing
wave	numeric	4 unique values 0 missing
tx	numeric	2 unique values 0 missing
reveal	numeric	3 unique values 0 missing
call	numeric	2 unique values 0 missing
laryngoscopi	numeric	3 unique values 0 missing
parallel	numeric	2 unique values 0 missing
hydrogen	numeric	2 unique values 0 missing
gener	numeric	3 unique values 0 missing
stimulatori	numeric	3 unique values 0 missing
review	numeric	4 unique values 0 missing
limb	numeric	4 unique values 0 missing
manner	numeric	2 unique values 0 missing
laryngectomi	numeric	3 unique values 0 missing
do	numeric	2 unique values 0 missing
thromboemboli	numeric	2 unique values 0 missing
freedom	numeric	5 unique values 0 missing
verifi	numeric	2 unique values 0 missing
layer	numeric	5 unique values 0 missing
preclin	numeric	2 unique values 0 missing
somat	numeric	2 unique values 0 missing
genet	numeric	5 unique values 0 missing
philosophi	numeric	2 unique values 0 missing
bruch	numeric	3 unique values 0 missing
carcinoma	numeric	7 unique values 0 missing
medic	numeric	9 unique values 0 missing
disclos	numeric	4 unique values 0 missing
dr	numeric	3 unique values 0 missing
aetiolog	numeric	2 unique values 0 missing
autonom	numeric	3 unique values 0 missing
defin	numeric	4 unique values 0 missing
cricoarytenoid	numeric	3 unique values 0 missing
treatabl	numeric	3 unique values 0 missing
workup	numeric	3 unique values 0 missing
lipoprotein	numeric	4 unique values 0 missing
treate	numeric	5 unique values 0 missing
scor	numeric	3 unique values 0 missing
outlin	numeric	2 unique values 0 missing
opportun	numeric	3 unique values 0 missing
histologi	numeric	2 unique values 0 missing
uveiti	numeric	2 unique values 0 missing
possibl	numeric	3 unique values 0 missing
unilater	numeric	3 unique values 0 missing
introduc	numeric	3 unique values 0 missing
harada	numeric	4 unique values 0 missing
highlight	numeric	2 unique values 0 missing
teflon	numeric	2 unique values 0 missing
abil	numeric	4 unique values 0 missing
death	numeric	10 unique values 0 missing
closur	numeric	4 unique values 0 missing
voluntari	numeric	3 unique values 0 missing
school	numeric	7 unique values 0 missing
refer	numeric	6 unique values 0 missing
abort	numeric	6 unique values 0 missing
uk	numeric	3 unique values 0 missing
post	numeric	5 unique values 0 missing
efflux	numeric	3 unique values 0 missing
excision	numeric	4 unique values 0 missing
endoscop	numeric	4 unique values 0 missing
matur	numeric	3 unique values 0 missing
echocardiogram	numeric	3 unique values 0 missing
neuropatholog	numeric	3 unique values 0 missing
fresh	numeric	3 unique values 0 missing
oil	numeric	7 unique values 0 missing
cardiopulmonari	numeric	5 unique values 0 missing
predominantli	numeric	3 unique values 0 missing
fewer	numeric	3 unique values 0 missing
subcutan	numeric	2 unique values 0 missing
variat	numeric	5 unique values 0 missing
choice	numeric	5 unique values 0 missing
affin	numeric	7 unique values 0 missing
serial	numeric	3 unique values 0 missing
antibodi	numeric	7 unique values 0 missing
option	numeric	3 unique values 0 missing
commissurotomi	numeric	3 unique values 0 missing
mental	numeric	3 unique values 0 missing
electrocardiogram	numeric	3 unique values 0 missing
little	numeric	3 unique values 0 missing
extract	numeric	3 unique values 0 missing
england	numeric	5 unique values 0 missing
us	numeric	4 unique values 0 missing
affect	numeric	5 unique values 0 missing
prematur	numeric	4 unique values 0 missing
reduct	numeric	7 unique values 0 missing
intim	numeric	3 unique values 0 missing
frequent	numeric	5 unique values 0 missing
recov	numeric	4 unique values 0 missing
possess	numeric	2 unique values 0 missing
aortic	numeric	12 unique values 0 missing
equilibrium	numeric	3 unique values 0 missing
exceed	numeric	4 unique values 0 missing
establish	numeric	3 unique values 0 missing
dy	numeric	4 unique values 0 missing
detach	numeric	6 unique values 0 missing
glutam	numeric	4 unique values 0 missing
lipid	numeric	6 unique values 0 missing
inhibit	numeric	7 unique values 0 missing
transloc	numeric	2 unique values 0 missing
porcin	numeric	6 unique values 0 missing
ineffect	numeric	2 unique values 0 missing
undergo	numeric	3 unique values 0 missing
suspect	numeric	4 unique values 0 missing
evid	numeric	4 unique values 0 missing
route	numeric	4 unique values 0 missing
polici	numeric	8 unique values 0 missing
dimens	numeric	4 unique values 0 missing
malform	numeric	3 unique values 0 missing
raw	numeric	2 unique values 0 missing
contemporari	numeric	2 unique values 0 missing
regurgit	numeric	8 unique values 0 missing
complaint	numeric	2 unique values 0 missing
mainten	numeric	2 unique values 0 missing
barrier	numeric	3 unique values 0 missing
scatter	numeric	2 unique values 0 missing
expos	numeric	4 unique values 0 missing
line	numeric	3 unique values 0 missing
strain	numeric	4 unique values 0 missing
calcif	numeric	5 unique values 0 missing
competit	numeric	4 unique values 0 missing
myoglobin	numeric	4 unique values 0 missing
quantiti	numeric	2 unique values 0 missing
kei	numeric	2 unique values 0 missing
specialist	numeric	4 unique values 0 missing
subretin	numeric	7 unique values 0 missing

Show first 100 features

107 properties

NumberOfInstances

1003

Number of instances (rows) of the dataset.

NumberOfFeatures

3183

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

3182

Number of numeric attributes.

NumberOfSymbolicFeatures

Number of nominal attributes.

Quartile1SkewnessOfNumericAtts

10.73

First quartile of skewness among attributes of the numeric type.

REPTreeDepth1Kappa

0.7

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

CfsSubsetEval_kNN1NAUC

0.93

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

0.22

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

0.19

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

0.55

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

J48.001.Kappa

0.75

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

MeanSkewnessOfNumericAtts

15.02

Mean skewness among attributes of the numeric type.

Quartile2AttributeEntropy

Second quartile (Median) of entropy among attributes.

REPTreeDepth2ErrRate

0.26

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

CfsSubsetEval_kNN1NKappa

0.78

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

0.81

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

MajorityClassPercentage

19.34

Percentage of instances belonging to the most frequent class.

MeanStdDevOfNumericAtts

0.21

Mean standard deviation of attributes of the numeric type.

Quartile2KurtosisOfNumericAtts

246.99

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

REPTreeDepth2Kappa

0.7

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

ClassEntropy

3.15

Entropy of the target attribute values.

kNN1NKappa

0.06

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

MajorityClassSize

194

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

0.66

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump

MaxAttributeEntropy

Maximum entropy among attributes.

MinKurtosisOfNumericAtts

3.56

Minimum kurtosis among attributes of the numeric type.

Quartile2MutualInformation

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

REPTreeDepth3ErrRate

0.26

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

DecisionStumpErrRate

0.65

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

MaxKurtosisOfNumericAtts

943.43

Maximum kurtosis among attributes of the numeric type.

MinMeansOfNumericAtts

Minimum of means among attributes of the numeric type.

Quartile2SkewnessOfNumericAtts

15.39

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

REPTreeDepth3Kappa

0.7

Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3

DecisionStumpKappa

0.21

Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump

MaxMeansOfNumericAtts

2.09

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

0.14

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

RandomTreeDepth1AUC

0.69

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

Dimensionality

3.17

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

0.54

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

1.82

Minimum skewness among attributes of the numeric type.

PercentageOfMissingValues

Percentage of missing values.

Quartile3KurtosisOfNumericAtts

375.73

Third quartile of kurtosis among attributes of the numeric type.

AutoCorrelation

0.34

Average class difference between consecutive instances.

RandomTreeDepth1Kappa

0.39

Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1

J48.00001.AUC

0.89

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001

MaxSkewnessOfNumericAtts

30.36

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

0.93

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

0.69

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

J48.00001.ErrRate

0.22

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

MaxStdDevOfNumericAtts

3.11

Maximum standard deviation of attributes of the numeric type.

MinorityClassPercentage

5.08

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

0.19

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

0.54

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

J48.00001.Kappa

0.75

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

18.23

Third quartile of skewness among attributes of the numeric type.

CfsSubsetEval_DecisionStumpKappa

0.78

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

0.39

Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2

J48.0001.AUC

0.89

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001

MeanKurtosisOfNumericAtts

279.43

Mean kurtosis among attributes of the numeric type.

NaiveBayesAUC

0.94

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

Quartile1KurtosisOfNumericAtts

129.27

First quartile of kurtosis among attributes of the numeric type.

Quartile3StdDevOfNumericAtts

0.26

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

CfsSubsetEval_NaiveBayesAUC

0.93

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

0.69

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

J48.0001.ErrRate

0.22

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

0.25

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

0.19

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

0.54

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

J48.0001.Kappa

0.75

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

0.72

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

0.26

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

CfsSubsetEval_NaiveBayesKappa

0.78

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

0.39

Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3

J48.001.AUC

0.89

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.

Show all 107 properties

63 tasks

Supervised Classification on oh0.wc

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

Supervised Classification on oh0.wc

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

Supervised Classification on oh0.wc

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

Supervised Regression on oh0.wc

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

Supervised Regression on oh0.wc

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

Supervised Regression on oh0.wc

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

Supervised Regression on oh0.wc

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

Supervised Regression on oh0.wc

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

Supervised Regression on oh0.wc

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

Supervised Regression on oh0.wc

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

Learning Curve on oh0.wc

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

Supervised Data Stream Classification on oh0.wc

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

Clustering on oh0.wc

0 runs - estimation_procedure: 50 times Clustering

Clustering on oh0.wc

0 runs - estimation_procedure: 50 times Clustering

Clustering on oh0.wc

0 runs - estimation_procedure: 50 times Clustering

Clustering on oh0.wc

0 runs - estimation_procedure: 50 times Clustering

Clustering on oh0.wc

0 runs - estimation_procedure: 50 times Clustering

Clustering on oh0.wc

0 runs

Clustering on oh0.wc

0 runs - estimation_procedure: 50 times Clustering

Clustering on oh0.wc

0 runs - estimation_procedure: 50 times Clustering

Clustering on oh0.wc

0 runs - estimation_procedure: 50 times Clustering

Clustering on oh0.wc

0 runs - estimation_procedure: 50 times Clustering

Clustering on oh0.wc

0 runs - estimation_procedure: 50 times Clustering

Subgroup Discovery on oh0.wc