Data
oh5.wc

oh5.wc

active Sparse_ARFF Publicly available Visibility: public Uploaded 28-09-2014 by Joaquin Vanschoren
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Author: [George Forman](https://scholar.google.com/citations?user=r0a222QAAAAJ) Source: http://tunedit.org/repo/Data/Text-wc/oh5.wc.arff Please cite:

3013 features

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optimumnumeric2 unique values
0 missing
stimulnumeric8 unique values
0 missing
yrnumeric2 unique values
0 missing
hyperlipidemianumeric2 unique values
0 missing
anastomosinumeric3 unique values
0 missing
targetnumeric3 unique values
0 missing
hospitnumeric6 unique values
0 missing
surfactnumeric8 unique values
0 missing
junenumeric2 unique values
0 missing
reviewnumeric3 unique values
0 missing
neurobehaviornumeric3 unique values
0 missing
integrnumeric4 unique values
0 missing
hematomanumeric4 unique values
0 missing
gynumeric3 unique values
0 missing
keratoplastinumeric5 unique values
0 missing
kinasnumeric6 unique values
0 missing
labelnumeric7 unique values
0 missing
analysnumeric3 unique values
0 missing
predisposnumeric3 unique values
0 missing
mammogramnumeric4 unique values
0 missing
tnumeric2 unique values
0 missing
scornumeric2 unique values
0 missing
urinarinumeric6 unique values
0 missing
girlnumeric3 unique values
0 missing
causenumeric4 unique values
0 missing
centernumeric3 unique values
0 missing
nmolnumeric4 unique values
0 missing
ursodeoxycholnumeric6 unique values
0 missing
mannitolnumeric5 unique values
0 missing
tinnitunumeric4 unique values
0 missing
performnumeric5 unique values
0 missing
accordinglinumeric2 unique values
0 missing
vnumeric8 unique values
0 missing
closurnumeric2 unique values
0 missing
isotopnumeric2 unique values
0 missing
purifinumeric5 unique values
0 missing
observnumeric5 unique values
0 missing
depletionnumeric3 unique values
0 missing
coefficinumeric3 unique values
0 missing
desaturnumeric3 unique values
0 missing
fundamentnumeric2 unique values
0 missing
serumnumeric8 unique values
0 missing
covernumeric3 unique values
0 missing
americannumeric3 unique values
0 missing
ammonianumeric4 unique values
0 missing
freshnumeric4 unique values
0 missing
enablnumeric2 unique values
0 missing
adenosinnumeric4 unique values
0 missing
refinnumeric2 unique values
0 missing
profilnumeric5 unique values
0 missing
incompatnumeric4 unique values
0 missing
qualitinumeric5 unique values
0 missing
reachnumeric2 unique values
0 missing
pulsatilnumeric3 unique values
0 missing
routinnumeric4 unique values
0 missing
nervenumeric7 unique values
0 missing
metabolnumeric9 unique values
0 missing
mentalnumeric4 unique values
0 missing
inductnumeric4 unique values
0 missing
bjorknumeric4 unique values
0 missing
prominnumeric3 unique values
0 missing
fuelnumeric3 unique values
0 missing
islandnumeric5 unique values
0 missing
handnumeric2 unique values
0 missing
indiumnumeric3 unique values
0 missing
analyznumeric2 unique values
0 missing
fourteennumeric2 unique values
0 missing
phosphatidylethanolaminnumeric3 unique values
0 missing
managnumeric6 unique values
0 missing
aorticnumeric5 unique values
0 missing
widespreadnumeric2 unique values
0 missing
flownumeric7 unique values
0 missing
psycholognumeric2 unique values
0 missing
hgnumeric4 unique values
0 missing
exchangnumeric4 unique values
0 missing
threatennumeric3 unique values
0 missing
foodnumeric4 unique values
0 missing
conductnumeric5 unique values
0 missing
pulsenumeric3 unique values
0 missing
erythromycinnumeric3 unique values
0 missing
vesiclnumeric7 unique values
0 missing
fasternumeric2 unique values
0 missing
abundnumeric3 unique values
0 missing
pmolnumeric5 unique values
0 missing
clonalnumeric4 unique values
0 missing
raisnumeric4 unique values
0 missing
consequnumeric3 unique values
0 missing
maximumnumeric3 unique values
0 missing
reactnumeric3 unique values
0 missing
subjectnumeric8 unique values
0 missing
centralnumeric3 unique values
0 missing
sizenumeric7 unique values
0 missing
vicenumeric2 unique values
0 missing
suspectnumeric5 unique values
0 missing
predictornumeric5 unique values
0 missing
barenumeric2 unique values
0 missing
promisnumeric2 unique values
0 missing
vacuumnumeric2 unique values
0 missing
makenumeric2 unique values
0 missing
animnumeric8 unique values
0 missing
validnumeric2 unique values
0 missing
intracerebrnumeric3 unique values
0 missing
timnumeric3 unique values
0 missing
crucialnumeric2 unique values
0 missing
omeganumeric2 unique values
0 missing
exposnumeric5 unique values
0 missing
existnumeric3 unique values
0 missing
hmgnumeric4 unique values
0 missing
repetitnumeric2 unique values
0 missing
respiratorinumeric5 unique values
0 missing
underestimnumeric3 unique values
0 missing
centrifugnumeric4 unique values
0 missing
footnumeric3 unique values
0 missing
outputnumeric4 unique values
0 missing
bladdernumeric5 unique values
0 missing
ablatnumeric4 unique values
0 missing
subclinnumeric3 unique values
0 missing
sixthnumeric2 unique values
0 missing
antiseranumeric4 unique values
0 missing
allograftnumeric9 unique values
0 missing
endotheliumnumeric4 unique values
0 missing
basnumeric5 unique values
0 missing
suggestnumeric4 unique values
0 missing
ipsilaternumeric2 unique values
0 missing
shiftnumeric3 unique values
0 missing
suboptimnumeric2 unique values
0 missing
precludnumeric2 unique values
0 missing
molnumeric3 unique values
0 missing
loudnumeric3 unique values
0 missing
sixtinumeric2 unique values
0 missing
undetectnumeric3 unique values
0 missing
globulinnumeric3 unique values
0 missing
autotransplantnumeric3 unique values
0 missing
trapnumeric2 unique values
0 missing
dailinumeric4 unique values
0 missing
catheternumeric4 unique values
0 missing
rationumeric7 unique values
0 missing
sumnumeric2 unique values
0 missing
adequnumeric3 unique values
0 missing
usagnumeric2 unique values
0 missing
consumnumeric3 unique values
0 missing
predispositnumeric2 unique values
0 missing
unirradinumeric3 unique values
0 missing
sensorineurnumeric5 unique values
0 missing
slightlinumeric3 unique values
0 missing
activnumeric12 unique values
0 missing
thrombinnumeric4 unique values
0 missing
chownumeric4 unique values
0 missing
reagentnumeric5 unique values
0 missing
termnumeric5 unique values
0 missing
aminonumeric10 unique values
0 missing
movnumeric2 unique values
0 missing
feasiblnumeric2 unique values
0 missing
gelnumeric5 unique values
0 missing
leukotriennumeric2 unique values
0 missing
subcellularnumeric5 unique values
0 missing
earliernumeric3 unique values
0 missing
aggravnumeric2 unique values
0 missing
transmissnumeric4 unique values
0 missing
coursenumeric5 unique values
0 missing
wastagnumeric2 unique values
0 missing
resolvnumeric3 unique values
0 missing
depressnumeric4 unique values
0 missing
catabolnumeric5 unique values
0 missing
outcomnumeric5 unique values
0 missing
justifinumeric2 unique values
0 missing
hybridnumeric4 unique values
0 missing
cochlearnumeric7 unique values
0 missing
episodnumeric5 unique values
0 missing
hrnumeric6 unique values
0 missing
pretreatnumeric5 unique values
0 missing
instrumnumeric2 unique values
0 missing
mumolnumeric5 unique values
0 missing
ldlnumeric6 unique values
0 missing
retestnumeric3 unique values
0 missing
notionnumeric2 unique values
0 missing
detectnumeric5 unique values
0 missing
elevennumeric2 unique values
0 missing
migratnumeric3 unique values
0 missing
deethylasnumeric3 unique values
0 missing
seminumeric2 unique values
0 missing
hznumeric7 unique values
0 missing
calmodulinnumeric4 unique values
0 missing
neverthelessnumeric2 unique values
0 missing
causnumeric5 unique values
0 missing
necessitnumeric2 unique values
0 missing
skillnumeric2 unique values
0 missing
ulcernumeric3 unique values
0 missing
irradinumeric8 unique values
0 missing
proteinnumeric15 unique values
0 missing
themselvnumeric2 unique values
0 missing
novelnumeric2 unique values
0 missing
extracraninumeric3 unique values
0 missing
kneenumeric2 unique values
0 missing
znnumeric3 unique values
0 missing
biolognumeric2 unique values
0 missing
antithyroidnumeric2 unique values
0 missing
consecutnumeric3 unique values
0 missing
saphennumeric5 unique values
0 missing
plateletnumeric9 unique values
0 missing
participnumeric3 unique values
0 missing
membrannumeric12 unique values
0 missing
pilotnumeric3 unique values
0 missing
adversnumeric3 unique values
0 missing
phasenumeric6 unique values
0 missing
mousenumeric3 unique values
0 missing
transitionnumeric4 unique values
0 missing
scorenumeric6 unique values
0 missing
towardnumeric3 unique values
0 missing
servenumeric3 unique values
0 missing
interventnumeric6 unique values
0 missing
morbidnumeric4 unique values
0 missing
treatenumeric6 unique values
0 missing
cerebrovascularnumeric3 unique values
0 missing
angiographinumeric4 unique values
0 missing
ethanolnumeric10 unique values
0 missing
fetunumeric2 unique values
0 missing
adhesionnumeric4 unique values
0 missing
guidenumeric2 unique values
0 missing
cfunumeric5 unique values
0 missing
microscopinumeric3 unique values
0 missing
constructnumeric2 unique values
0 missing
mediumnumeric5 unique values
0 missing
headachnumeric4 unique values
0 missing
deathnumeric5 unique values
0 missing
resonnumeric4 unique values
0 missing
statistnumeric4 unique values
0 missing
tumournumeric3 unique values
0 missing
underwnumeric4 unique values
0 missing
aminotransferasnumeric3 unique values
0 missing
phenobarbitnumeric3 unique values
0 missing
monkeinumeric4 unique values
0 missing
myocardinumeric6 unique values
0 missing
quantitnumeric4 unique values
0 missing
intubnumeric4 unique values
0 missing
antiplateletnumeric5 unique values
0 missing
unsatisfactorinumeric2 unique values
0 missing
latternumeric2 unique values
0 missing
lactogennumeric2 unique values
0 missing
branchnumeric5 unique values
0 missing
waitnumeric3 unique values
0 missing
ienumeric2 unique values
0 missing
therapeutnumeric3 unique values
0 missing
autogennumeric4 unique values
0 missing
dramatnumeric2 unique values
0 missing
insteadnumeric2 unique values
0 missing
cystnumeric4 unique values
0 missing
supplementnumeric5 unique values
0 missing
undergonumeric4 unique values
0 missing
verticnumeric3 unique values
0 missing
illustrnumeric2 unique values
0 missing
basenumeric4 unique values
0 missing
isolnumeric4 unique values
0 missing
ignumeric9 unique values
0 missing
phenomenonnumeric4 unique values
0 missing
exposurnumeric7 unique values
0 missing
trypsinnumeric3 unique values
0 missing
predictnumeric6 unique values
0 missing
estrogennumeric6 unique values
0 missing
dilatnumeric3 unique values
0 missing
scatternumeric4 unique values
0 missing
arisnumeric2 unique values
0 missing
naivenumeric3 unique values
0 missing
basinumeric3 unique values
0 missing
isomnumeric2 unique values
0 missing
distressnumeric3 unique values
0 missing
difficultnumeric2 unique values
0 missing
nucleotidasnumeric3 unique values
0 missing
tracernumeric3 unique values
0 missing
mrnanumeric2 unique values
0 missing
preparnumeric5 unique values
0 missing
childhoodnumeric4 unique values
0 missing
polyacrylamidnumeric2 unique values
0 missing
closnumeric5 unique values
0 missing
anastomosnumeric3 unique values
0 missing
gradenumeric6 unique values
0 missing
osseounumeric3 unique values
0 missing
osmotnumeric5 unique values
0 missing
malenumeric6 unique values
0 missing
transformnumeric4 unique values
0 missing
distalnumeric4 unique values
0 missing
lednumeric3 unique values
0 missing
symptomatnumeric4 unique values
0 missing
agglutininnumeric2 unique values
0 missing
cascadnumeric3 unique values
0 missing
bolunumeric4 unique values
0 missing
anastomotnumeric4 unique values
0 missing
conceivnumeric2 unique values
0 missing
endocardnumeric4 unique values
0 missing
iinumeric7 unique values
0 missing
conservnumeric4 unique values
0 missing
rianumeric3 unique values
0 missing
fortinumeric2 unique values
0 missing
legnumeric3 unique values
0 missing
vocalnumeric4 unique values
0 missing
flexionnumeric4 unique values
0 missing
greatlinumeric2 unique values
0 missing
clotnumeric4 unique values
0 missing
inhernumeric2 unique values
0 missing
constantnumeric3 unique values
0 missing
prolongnumeric6 unique values
0 missing
offernumeric3 unique values
0 missing
impressnumeric2 unique values
0 missing
ribnumeric4 unique values
0 missing
electrolytnumeric3 unique values
0 missing
intracoronarinumeric2 unique values
0 missing
chimernumeric4 unique values
0 missing
tibialnumeric3 unique values
0 missing
incompletnumeric2 unique values
0 missing
avoidnumeric4 unique values
0 missing
rectalnumeric3 unique values
0 missing
priornumeric3 unique values
0 missing
mitochondrianumeric6 unique values
0 missing
importantlinumeric2 unique values
0 missing
montenumeric3 unique values
0 missing
autoimmunnumeric5 unique values
0 missing
thromboembolnumeric6 unique values
0 missing
favornumeric3 unique values
0 missing
atherosclerotnumeric3 unique values
0 missing
immunodeficinumeric5 unique values
0 missing
sequentinumeric3 unique values
0 missing
mmolnumeric4 unique values
0 missing
supportnumeric5 unique values
0 missing
timenumeric6 unique values
0 missing
fibrinogennumeric3 unique values
0 missing
createnumeric3 unique values
0 missing
monthnumeric7 unique values
0 missing
probablnumeric3 unique values
0 missing
remissnumeric3 unique values
0 missing
duenumeric4 unique values
0 missing
anthropometrnumeric4 unique values
0 missing
potentnumeric3 unique values
0 missing
isonitrogennumeric3 unique values
0 missing
pathogenesinumeric3 unique values
0 missing
commonlinumeric2 unique values
0 missing
glucagonnumeric4 unique values
0 missing
stopnumeric2 unique values
0 missing
underscornumeric2 unique values
0 missing
emulsnumeric4 unique values
0 missing
cgynumeric3 unique values
0 missing
motionnumeric5 unique values
0 missing
intravascularnumeric3 unique values
0 missing
fillnumeric3 unique values
0 missing
kcalnumeric5 unique values
0 missing
nadnumeric3 unique values
0 missing
titratnumeric2 unique values
0 missing
carotidnumeric8 unique values
0 missing
rectumnumeric3 unique values
0 missing
correlnumeric7 unique values
0 missing
ilnumeric5 unique values
0 missing
mothernumeric5 unique values
0 missing
postinjectnumeric2 unique values
0 missing
dentalnumeric5 unique values
0 missing
lennumeric3 unique values
0 missing
independnumeric4 unique values
0 missing
womannumeric3 unique values
0 missing
probenumeric5 unique values
0 missing
utilnumeric4 unique values
0 missing
catecholaminnumeric3 unique values
0 missing

107 properties

918
Number of instances (rows) of the dataset.
3013
Number of attributes (columns) of the dataset.
10
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
3012
Number of numeric attributes.
1
Number of nominal attributes.
Second quartile (Median) of entropy among attributes.
0.22
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.73
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
0.82
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
16.23
Percentage of instances belonging to the most frequent class.
0.22
Mean standard deviation of attributes of the numeric type.
225.74
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.75
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
3.24
Entropy of the target attribute values.
0.07
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
149
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
0.01
Second quartile (Median) of means among attributes of the numeric type.
0.94
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.61
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum entropy among attributes.
4.96
Minimum kurtosis among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.22
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.75
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
901.89
Maximum kurtosis among attributes of the numeric type.
0
Minimum of means among attributes of the numeric type.
14.51
Second quartile (Median) of skewness among attributes of the numeric type.
0.75
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.11
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
1.7
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of binary attributes.
0.16
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.62
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
3.28
Number of attributes divided by the number of instances.
Maximum mutual information between the nominal attributes and the target attribute.
10
The minimal number of distinct values among attributes of the nominal type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
0.69
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
10
The maximum number of distinct values among attributes of the nominal type.
1.85
Minimum skewness among attributes of the numeric type.
0
Percentage of missing values.
353.17
Third quartile of kurtosis among attributes of the numeric type.
0.23
Average class difference between consecutive instances.
0.23
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.89
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
29.92
Maximum skewness among attributes of the numeric type.
0.06
Minimum standard deviation of attributes of the numeric type.
99.97
Percentage of numeric attributes.
0.03
Third quartile of means among attributes of the numeric type.
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
0.62
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.21
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
3.71
Maximum standard deviation of attributes of the numeric type.
6.43
Percentage of instances belonging to the least frequent class.
0.03
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
0.24
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
0.69
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.77
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Average entropy of the attributes.
59
Number of instances belonging to the least frequent class.
First quartile of entropy among attributes.
17.94
Third quartile of skewness among attributes of the numeric type.
0.73
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
0.23
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.89
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
260.51
Mean kurtosis among attributes of the numeric type.
0.93
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
117.76
First quartile of kurtosis among attributes of the numeric type.
0.27
Third quartile of standard deviation of attributes of the numeric type.
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
0.62
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.21
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0.03
Mean of means among attributes of the numeric type.
0.28
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.01
First quartile of means among attributes of the numeric type.
0.94
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.24
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
0.69
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.77
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Average mutual information between the nominal attributes and the target attribute.
0.69
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of mutual information between the nominal attributes and the target attribute.
0.22
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.73
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
0.23
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.89
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
0
Number of binary attributes.
10.26
First quartile of skewness among attributes of the numeric type.
0.75
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
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
0
Standard deviation of the number of distinct values among attributes of the nominal type.
0.21
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
10
Average number of distinct values among the attributes of the nominal type.
0.09
First quartile of standard deviation of attributes of the numeric type.
0.94
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.24
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
0.54
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.77
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
14.46
Mean skewness among attributes of the numeric type.

51 tasks

242 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: CLASS_LABEL
92 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: CLASS_LABEL
0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: mean_absolute_error - target_feature: class
0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: mean_absolute_error - target_feature: class
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
39 runs - estimation_procedure: 10-fold Learning Curve - target_feature: CLASS_LABEL
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: CLASS_LABEL
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - target_feature: CLASS_LABEL
0 runs - target_feature: CLASS_LABEL
0 runs - target_feature: CLASS_LABEL
0 runs - target_feature: CLASS_LABEL
0 runs - target_feature: CLASS_LABEL
0 runs - target_feature: CLASS_LABEL
0 runs - target_feature: CLASS_LABEL
0 runs - target_feature: CLASS_LABEL
0 runs - target_feature: CLASS_LABEL
0 runs - target_feature: CLASS_LABEL
0 runs - target_feature: CLASS_LABEL
0 runs - target_feature: CLASS_LABEL
0 runs - target_feature: CLASS_LABEL
0 runs - target_feature: CLASS_LABEL
0 runs - target_feature: CLASS_LABEL
0 runs - target_feature: CLASS_LABEL
0 runs - target_feature: CLASS_LABEL
0 runs - target_feature: CLASS_LABEL
0 runs - target_feature: CLASS_LABEL
0 runs - target_feature: CLASS_LABEL
0 runs - target_feature: CLASS_LABEL
0 runs - target_feature: CLASS_LABEL
0 runs - target_feature: CLASS_LABEL
0 runs - target_feature: CLASS_LABEL
0 runs - target_feature: CLASS_LABEL
0 runs - target_feature: CLASS_LABEL
0 runs - target_feature: CLASS_LABEL
0 runs - target_feature: CLASS_LABEL
0 runs - target_feature: CLASS_LABEL
0 runs - target_feature: CLASS_LABEL
0 runs - target_feature: CLASS_LABEL
0 runs - target_feature: CLASS_LABEL
0 runs - target_feature: CLASS_LABEL
0 runs - target_feature: CLASS_LABEL
0 runs - target_feature: CLASS_LABEL
0 runs - target_feature: CLASS_LABEL
0 runs - target_feature: CLASS_LABEL
0 runs - target_feature: CLASS_LABEL
0 runs - target_feature: CLASS_LABEL
0 runs - target_feature: CLASS_LABEL
Define a new task