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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)	nominal	10 unique values 0 missing
cluster	numeric	3 unique values 0 missing
plai	numeric	4 unique values 0 missing
acut	numeric	7 unique values 0 missing
densiti	numeric	7 unique values 0 missing
nuclei	numeric	3 unique values 0 missing
al	numeric	10 unique values 0 missing
grow	numeric	4 unique values 0 missing
radic	numeric	3 unique values 0 missing
report	numeric	7 unique values 0 missing
advanc	numeric	3 unique values 0 missing
intim	numeric	4 unique values 0 missing
extern	numeric	4 unique values 0 missing
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infus	numeric	4 unique values 0 missing
identifi	numeric	4 unique values 0 missing
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own	numeric	2 unique values 0 missing
parenchym	numeric	2 unique values 0 missing
am	numeric	5 unique values 0 missing
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prefer	numeric	3 unique values 0 missing
csf	numeric	9 unique values 0 missing
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killer	numeric	2 unique values 0 missing
respect	numeric	6 unique values 0 missing
stenos	numeric	3 unique values 0 missing
gland	numeric	4 unique values 0 missing
presenc	numeric	5 unique values 0 missing
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chemic	numeric	3 unique values 0 missing
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immatur	numeric	5 unique values 0 missing
orient	numeric	3 unique values 0 missing
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alter	numeric	5 unique values 0 missing
coronari	numeric	9 unique values 0 missing
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vasospasm	numeric	2 unique values 0 missing
cerebellar	numeric	4 unique values 0 missing
stimulu	numeric	3 unique values 0 missing
suppli	numeric	3 unique values 0 missing
terminu	numeric	2 unique values 0 missing
thorac	numeric	2 unique values 0 missing
temperatur	numeric	5 unique values 0 missing
highli	numeric	3 unique values 0 missing
randomli	numeric	2 unique values 0 missing
solubl	numeric	3 unique values 0 missing
balanc	numeric	6 unique values 0 missing
slowli	numeric	2 unique values 0 missing
procee	numeric	2 unique values 0 missing
blockag	numeric	2 unique values 0 missing
introduct	numeric	2 unique values 0 missing
cation	numeric	4 unique values 0 missing
region	numeric	6 unique values 0 missing
marker	numeric	5 unique values 0 missing
column	numeric	3 unique values 0 missing
compens	numeric	3 unique values 0 missing
capd	numeric	6 unique values 0 missing
benzodiazepin	numeric	4 unique values 0 missing
thymocyt	numeric	3 unique values 0 missing
reminisc	numeric	4 unique values 0 missing
manag	numeric	5 unique values 0 missing
understand	numeric	3 unique values 0 missing
predomin	numeric	3 unique values 0 missing
physiolog	numeric	4 unique values 0 missing
shortli	numeric	2 unique values 0 missing
da	numeric	4 unique values 0 missing
tobramycin	numeric	4 unique values 0 missing
lethal	numeric	2 unique values 0 missing
narrow	numeric	2 unique values 0 missing
epinephrin	numeric	5 unique values 0 missing
blunt	numeric	3 unique values 0 missing
ideal	numeric	3 unique values 0 missing
metabol	numeric	8 unique values 0 missing
accessori	numeric	4 unique values 0 missing
angiograph	numeric	3 unique values 0 missing
zealand	numeric	3 unique values 0 missing
behav	numeric	2 unique values 0 missing
de	numeric	4 unique values 0 missing
tf	numeric	5 unique values 0 missing
lipopolysaccharid	numeric	4 unique values 0 missing
passag	numeric	3 unique values 0 missing
dna	numeric	11 unique values 0 missing
guid	numeric	2 unique values 0 missing
context	numeric	3 unique values 0 missing
vesicl	numeric	2 unique values 0 missing
acet	numeric	4 unique values 0 missing
attain	numeric	2 unique values 0 missing
stain	numeric	6 unique values 0 missing
phosphoru	numeric	4 unique values 0 missing
di	numeric	5 unique values 0 missing
angioplasti	numeric	4 unique values 0 missing
colon	numeric	5 unique values 0 missing
amplitud	numeric	3 unique values 0 missing
entir	numeric	2 unique values 0 missing
tcr	numeric	8 unique values 0 missing
adrenoceptor	numeric	3 unique values 0 missing
consum	numeric	4 unique values 0 missing
bovin	numeric	7 unique values 0 missing
length	numeric	5 unique values 0 missing
media	numeric	5 unique values 0 missing
sulfat	numeric	5 unique values 0 missing
hydrophob	numeric	4 unique values 0 missing
th	numeric	3 unique values 0 missing
technic	numeric	2 unique values 0 missing
regener	numeric	3 unique values 0 missing
dietari	numeric	4 unique values 0 missing
exhibit	numeric	4 unique values 0 missing
nare	numeric	3 unique values 0 missing
feasibl	numeric	2 unique values 0 missing
single	numeric	5 unique values 0 missing
limb	numeric	5 unique values 0 missing
tendenc	numeric	3 unique values 0 missing
histologi	numeric	3 unique values 0 missing
dl	numeric	7 unique values 0 missing
ti	numeric	4 unique values 0 missing
classic	numeric	2 unique values 0 missing
pain	numeric	4 unique values 0 missing
ristocetin	numeric	4 unique values 0 missing
urea	numeric	7 unique values 0 missing
organel	numeric	3 unique values 0 missing
outcom	numeric	4 unique values 0 missing
preserv	numeric	3 unique values 0 missing
carcinoma	numeric	5 unique values 0 missing
manner	numeric	4 unique values 0 missing
febril	numeric	2 unique values 0 missing
ambulatori	numeric	4 unique values 0 missing
elimin	numeric	4 unique values 0 missing
classif	numeric	3 unique values 0 missing
preval	numeric	4 unique values 0 missing
increas	numeric	13 unique values 0 missing
commun	numeric	5 unique values 0 missing
overal	numeric	4 unique values 0 missing
detect	numeric	6 unique values 0 missing
help	numeric	3 unique values 0 missing
phosphatid	numeric	4 unique values 0 missing
medic	numeric	5 unique values 0 missing
refer	numeric	4 unique values 0 missing
ligat	numeric	4 unique values 0 missing
decemb	numeric	2 unique values 0 missing
postop	numeric	6 unique values 0 missing
pair	numeric	5 unique values 0 missing
dialys	numeric	5 unique values 0 missing
tube	numeric	4 unique values 0 missing
agonist	numeric	7 unique values 0 missing
irradi	numeric	5 unique values 0 missing
prove	numeric	2 unique values 0 missing
oil	numeric	4 unique values 0 missing
opportun	numeric	2 unique values 0 missing
predominantli	numeric	3 unique values 0 missing
wave	numeric	4 unique values 0 missing
centre	numeric	3 unique values 0 missing
lactamas	numeric	4 unique values 0 missing
lesser	numeric	2 unique values 0 missing
supplem	numeric	3 unique values 0 missing
source	numeric	4 unique values 0 missing
mhc	numeric	5 unique values 0 missing
particip	numeric	3 unique values 0 missing
cancer	numeric	5 unique values 0 missing
neurotox	numeric	3 unique values 0 missing
embryo	numeric	3 unique values 0 missing
preincub	numeric	4 unique values 0 missing
dr	numeric	3 unique values 0 missing
delta	numeric	7 unique values 0 missing
hplc	numeric	3 unique values 0 missing
biosynthesi	numeric	3 unique values 0 missing
spe	numeric	3 unique values 0 missing
supernat	numeric	4 unique values 0 missing
overload	numeric	4 unique values 0 missing
stimulatori	numeric	5 unique values 0 missing
review	numeric	3 unique values 0 missing
equilibrium	numeric	3 unique values 0 missing
little	numeric	3 unique values 0 missing
phosphatidyl	numeric	3 unique values 0 missing
fewer	numeric	2 unique values 0 missing
fura	numeric	2 unique values 0 missing
absenc	numeric	4 unique values 0 missing
indirect	numeric	3 unique values 0 missing
blue	numeric	4 unique values 0 missing
malign	numeric	4 unique values 0 missing
typ	numeric	2 unique values 0 missing
jejunum	numeric	3 unique values 0 missing
fresh	numeric	3 unique values 0 missing
evid	numeric	4 unique values 0 missing
exceed	numeric	3 unique values 0 missing
herein	numeric	2 unique values 0 missing
increm	numeric	3 unique values 0 missing
possibl	numeric	3 unique values 0 missing
nonhydrolyz	numeric	2 unique values 0 missing
share	numeric	2 unique values 0 missing
final	numeric	3 unique values 0 missing
urem	numeric	10 unique values 0 missing
prothrombot	numeric	3 unique values 0 missing
treate	numeric	8 unique values 0 missing
closur	numeric	3 unique values 0 missing
line	numeric	7 unique values 0 missing
route	numeric	2 unique values 0 missing
extract	numeric	5 unique values 0 missing
dimens	numeric	3 unique values 0 missing
transurethr	numeric	3 unique values 0 missing
permit	numeric	2 unique values 0 missing
hemorrhag	numeric	6 unique values 0 missing
dialyz	numeric	3 unique values 0 missing
stable	numeric	4 unique values 0 missing
surgeri	numeric	7 unique values 0 missing
death	numeric	5 unique values 0 missing
gdp	numeric	4 unique values 0 missing
intracrani	numeric	3 unique values 0 missing
cortisol	numeric	5 unique values 0 missing
amp	numeric	6 unique values 0 missing
competit	numeric	2 unique values 0 missing
subcutan	numeric	5 unique values 0 missing
permeabil	numeric	4 unique values 0 missing
fold	numeric	6 unique values 0 missing
denud	numeric	3 unique values 0 missing
unsuccess	numeric	2 unique values 0 missing
photoreceptor	numeric	4 unique values 0 missing
possess	numeric	3 unique values 0 missing
mental	numeric	5 unique values 0 missing
inoculum	numeric	2 unique values 0 missing
tomograph	numeric	4 unique values 0 missing
establish	numeric	3 unique values 0 missing
ion	numeric	5 unique values 0 missing
us	numeric	5 unique values 0 missing
ventil	numeric	3 unique values 0 missing
exert	numeric	2 unique values 0 missing
approxim	numeric	3 unique values 0 missing
embryon	numeric	4 unique values 0 missing
transmit	numeric	3 unique values 0 missing
undergo	numeric	4 unique values 0 missing
aortic	numeric	6 unique values 0 missing
evolv	numeric	2 unique values 0 missing
strain	numeric	9 unique values 0 missing
render	numeric	2 unique values 0 missing
luteal	numeric	3 unique values 0 missing
filam	numeric	5 unique values 0 missing
absent	numeric	3 unique values 0 missing
issue	numeric	2 unique values 0 missing
dog	numeric	8 unique values 0 missing
stabli	numeric	2 unique values 0 missing
site	numeric	8 unique values 0 missing
scatter	numeric	2 unique values 0 missing
oxacillin	numeric	5 unique values 0 missing
minut	numeric	7 unique values 0 missing
phorbol	numeric	8 unique values 0 missing
calcif	numeric	3 unique values 0 missing
spinal	numeric	5 unique values 0 missing
amnes	numeric	3 unique values 0 missing
recruit	numeric	4 unique values 0 missing
natur	numeric	3 unique values 0 missing
techniqu	numeric	5 unique values 0 missing
notabl	numeric	2 unique values 0 missing
libitum	numeric	3 unique values 0 missing
earliest	numeric	3 unique values 0 missing
microvasculatur	numeric	3 unique values 0 missing
link	numeric	7 unique values 0 missing
hemodialysi	numeric	6 unique values 0 missing
reproduc	numeric	3 unique values 0 missing
clear	numeric	2 unique values 0 missing
va	numeric	4 unique values 0 missing
result	numeric	6 unique values 0 missing
surprisingli	numeric	2 unique values 0 missing
conspicu	numeric	2 unique values 0 missing
phosphoinositid	numeric	5 unique values 0 missing
epithelium	numeric	4 unique values 0 missing
glass	numeric	2 unique values 0 missing
faster	numeric	2 unique values 0 missing
etiolog	numeric	3 unique values 0 missing
explor	numeric	2 unique values 0 missing
mucos	numeric	3 unique values 0 missing
prelabel	numeric	2 unique values 0 missing
third	numeric	3 unique values 0 missing
acetylcholin	numeric	3 unique values 0 missing
threshold	numeric	3 unique values 0 missing
dorsal	numeric	3 unique values 0 missing
somatostatin	numeric	3 unique values 0 missing
believ	numeric	2 unique values 0 missing
polyacrylamid	numeric	3 unique values 0 missing
suspect	numeric	3 unique values 0 missing
cellular	numeric	4 unique values 0 missing
respond	numeric	6 unique values 0 missing
disrupt	numeric	6 unique values 0 missing
ec	numeric	7 unique values 0 missing
carbohydr	numeric	3 unique values 0 missing
newli	numeric	2 unique values 0 missing
perfor	numeric	4 unique values 0 missing
dos	numeric	3 unique values 0 missing
scaveng	numeric	2 unique values 0 missing
mic	numeric	5 unique values 0 missing
uninfect	numeric	3 unique values 0 missing
expos	numeric	6 unique values 0 missing
alveolar	numeric	5 unique values 0 missing
spectroscopi	numeric	4 unique values 0 missing
experi	numeric	6 unique values 0 missing
primarili	numeric	2 unique values 0 missing
yag	numeric	3 unique values 0 missing
potenti	numeric	5 unique values 0 missing
summar	numeric	2 unique values 0 missing
fibrinolysi	numeric	2 unique values 0 missing
intox	numeric	3 unique values 0 missing
causal	numeric	2 unique values 0 missing
cascad	numeric	4 unique values 0 missing
sixth	numeric	2 unique values 0 missing
organ	numeric	6 unique values 0 missing
bacterem	numeric	4 unique values 0 missing
percent	numeric	6 unique values 0 missing
cleav	numeric	3 unique values 0 missing
beate	numeric	2 unique values 0 missing
immunoassai	numeric	2 unique values 0 missing
purul	numeric	2 unique values 0 missing
tend	numeric	2 unique values 0 missing
retent	numeric	5 unique values 0 missing
mid	numeric	4 unique values 0 missing
nosocomi	numeric	6 unique values 0 missing
flora	numeric	3 unique values 0 missing
increasingli	numeric	3 unique values 0 missing
anterior	numeric	4 unique values 0 missing
zymosan	numeric	4 unique values 0 missing
bradykinin	numeric	4 unique values 0 missing
water	numeric	4 unique values 0 missing
mild	numeric	3 unique values 0 missing
care	numeric	5 unique values 0 missing
particularli	numeric	2 unique values 0 missing
coval	numeric	3 unique values 0 missing
granulomat	numeric	3 unique values 0 missing
greatli	numeric	2 unique values 0 missing
gel	numeric	5 unique values 0 missing
neurobehavior	numeric	2 unique values 0 missing
respons	numeric	11 unique values 0 missing
ang	numeric	4 unique values 0 missing
eg	numeric	4 unique values 0 missing
unalt	numeric	3 unique values 0 missing
carboxi	numeric	3 unique values 0 missing
dissemin	numeric	3 unique values 0 missing
deletion	numeric	3 unique values 0 missing
osteoid	numeric	2 unique values 0 missing
isocalor	numeric	2 unique values 0 missing
incomplet	numeric	2 unique values 0 missing
infrequ	numeric	2 unique values 0 missing
urinari	numeric	4 unique values 0 missing
hla	numeric	2 unique values 0 missing
xanthin	numeric	3 unique values 0 missing
voltag	numeric	4 unique values 0 missing
monom	numeric	4 unique values 0 missing
bactericid	numeric	4 unique values 0 missing
crystal	numeric	4 unique values 0 missing
belong	numeric	3 unique values 0 missing
striatum	numeric	3 unique values 0 missing
adenyl	numeric	6 unique values 0 missing
sequenti	numeric	3 unique values 0 missing
eleven	numeric	2 unique values 0 missing
isotop	numeric	3 unique values 0 missing
futur	numeric	2 unique values 0 missing
pure	numeric	2 unique values 0 missing
thrombolysi	numeric	3 unique values 0 missing
multipl	numeric	5 unique values 0 missing
tetradecanoyl	numeric	3 unique values 0 missing
ubiquit	numeric	2 unique values 0 missing
proteolysi	numeric	4 unique values 0 missing
clarifi	numeric	2 unique values 0 missing
reject	numeric	4 unique values 0 missing
genom	numeric	2 unique values 0 missing
protein	numeric	13 unique values 0 missing
garnet	numeric	3 unique values 0 missing
consumpt	numeric	5 unique values 0 missing
instill	numeric	3 unique values 0 missing
ex	numeric	3 unique values 0 missing
revis	numeric	2 unique values 0 missing
irrevers	numeric	4 unique values 0 missing
surfac	numeric	9 unique values 0 missing
vasopressin	numeric	5 unique values 0 missing
hyperplasia	numeric	2 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

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

3100

Number of numeric attributes.

NumberOfSymbolicFeatures

Number of nominal attributes.

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

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

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

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

0.64

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

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

MinSkewnessOfNumericAtts

1.5

Minimum skewness among attributes of the numeric type.

PercentageOfMissingValues

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

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

Number of binary 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

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

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.

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