Data
oh10.wc

oh10.wc

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

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agglutinnumeric4 unique values
0 missing
vitreoretinopathinumeric4 unique values
0 missing
discontinunumeric2 unique values
0 missing
aspartnumeric2 unique values
0 missing
unstablnumeric3 unique values
0 missing
linenumeric5 unique values
0 missing
musculoskeletnumeric2 unique values
0 missing
molecularnumeric4 unique values
0 missing
preliminarinumeric3 unique values
0 missing
chromatographinumeric4 unique values
0 missing
breadnumeric3 unique values
0 missing
controllnumeric4 unique values
0 missing
titernumeric3 unique values
0 missing
folliclnumeric3 unique values
0 missing
rianumeric3 unique values
0 missing
screennumeric10 unique values
0 missing
meatenumeric3 unique values
0 missing
facilitnumeric2 unique values
0 missing
linknumeric2 unique values
0 missing
compromisnumeric2 unique values
0 missing
nanumeric5 unique values
0 missing
thermalnumeric3 unique values
0 missing
glucocorticoidnumeric3 unique values
0 missing
culturnumeric6 unique values
0 missing
relatnumeric8 unique values
0 missing
trialnumeric6 unique values
0 missing
holdnumeric2 unique values
0 missing
autoimmunnumeric3 unique values
0 missing
devicnumeric3 unique values
0 missing
bulknumeric2 unique values
0 missing
melanomanumeric2 unique values
0 missing
cellularnumeric4 unique values
0 missing
intermedinumeric4 unique values
0 missing
arrestnumeric6 unique values
0 missing
forcenumeric4 unique values
0 missing
anatomnumeric3 unique values
0 missing
malnutritnumeric4 unique values
0 missing
visionnumeric2 unique values
0 missing
fearnumeric2 unique values
0 missing
holenumeric4 unique values
0 missing
probablnumeric4 unique values
0 missing
pressnumeric2 unique values
0 missing
malarianumeric4 unique values
0 missing
cleavagnumeric3 unique values
0 missing
increasinglinumeric2 unique values
0 missing
developnumeric4 unique values
0 missing
assainumeric5 unique values
0 missing
enzymnumeric6 unique values
0 missing
collagennumeric5 unique values
0 missing
womennumeric8 unique values
0 missing
minernumeric3 unique values
0 missing
contrarinumeric2 unique values
0 missing
adhesionnumeric3 unique values
0 missing
totalnumeric8 unique values
0 missing
drynumeric3 unique values
0 missing
absorbnumeric3 unique values
0 missing
insultnumeric2 unique values
0 missing
isotopnumeric2 unique values
0 missing
aheadnumeric2 unique values
0 missing
ndnumeric4 unique values
0 missing
lipasnumeric4 unique values
0 missing
livnumeric4 unique values
0 missing
originnumeric5 unique values
0 missing
relaxnumeric5 unique values
0 missing
ultrasonographinumeric4 unique values
0 missing
distressnumeric2 unique values
0 missing
postulnumeric2 unique values
0 missing
devisnumeric2 unique values
0 missing
elutnumeric3 unique values
0 missing
fshnumeric4 unique values
0 missing
inductnumeric4 unique values
0 missing
parasitnumeric4 unique values
0 missing
ngnumeric6 unique values
0 missing
purifnumeric2 unique values
0 missing
databasnumeric4 unique values
0 missing
judgnumeric2 unique values
0 missing
twinnumeric5 unique values
0 missing
chorioretinnumeric3 unique values
0 missing
importantlinumeric2 unique values
0 missing
posturnumeric3 unique values
0 missing
satisfactnumeric3 unique values
0 missing
simplenumeric3 unique values
0 missing
dilutnumeric3 unique values
0 missing
abundnumeric3 unique values
0 missing
presumnumeric2 unique values
0 missing
modifinumeric3 unique values
0 missing
accountnumeric4 unique values
0 missing
perspectnumeric3 unique values
0 missing
nightnumeric5 unique values
0 missing
vigornumeric2 unique values
0 missing
couplenumeric5 unique values
0 missing
createnumeric3 unique values
0 missing
chinumeric3 unique values
0 missing
extravascularnumeric4 unique values
0 missing
dosenumeric7 unique values
0 missing
yorknumeric2 unique values
0 missing
fruitnumeric4 unique values
0 missing
lysonumeric3 unique values
0 missing
nmnumeric4 unique values
0 missing
variounumeric4 unique values
0 missing
alzheimnumeric6 unique values
0 missing
intracellularnumeric4 unique values
0 missing
arminumeric3 unique values
0 missing
expectnumeric6 unique values
0 missing
smoknumeric9 unique values
0 missing
abstractnumeric2 unique values
0 missing
physiologinumeric3 unique values
0 missing
wedgenumeric3 unique values
0 missing
azoospermianumeric3 unique values
0 missing
existnumeric3 unique values
0 missing
diabetnumeric8 unique values
0 missing
ntnumeric4 unique values
0 missing
updatnumeric3 unique values
0 missing
clonenumeric3 unique values
0 missing
pressurnumeric13 unique values
0 missing
inadequacinumeric2 unique values
0 missing
moleculnumeric3 unique values
0 missing
impairnumeric5 unique values
0 missing
chonumeric4 unique values
0 missing
targetnumeric4 unique values
0 missing
vasodilnumeric5 unique values
0 missing
usualnumeric3 unique values
0 missing
drinkernumeric3 unique values
0 missing
dystocianumeric3 unique values
0 missing
nynumeric2 unique values
0 missing
mesenternumeric6 unique values
0 missing
recipinumeric6 unique values
0 missing
antagonistnumeric7 unique values
0 missing
photographnumeric3 unique values
0 missing
regardnumeric3 unique values
0 missing
bilaternumeric3 unique values
0 missing
benefitnumeric5 unique values
0 missing
analysnumeric4 unique values
0 missing
ischemnumeric5 unique values
0 missing
bloodnumeric11 unique values
0 missing
sixfoldnumeric2 unique values
0 missing
regionnumeric6 unique values
0 missing
transportnumeric5 unique values
0 missing
italinumeric4 unique values
0 missing
fallnumeric7 unique values
0 missing
nutrientnumeric6 unique values
0 missing
suppressnumeric7 unique values
0 missing
pafnumeric6 unique values
0 missing
referrnumeric3 unique values
0 missing
hematopoietnumeric4 unique values
0 missing
analytnumeric4 unique values
0 missing
slowlinumeric2 unique values
0 missing
uterinnumeric4 unique values
0 missing
undetectnumeric2 unique values
0 missing
disclosnumeric2 unique values
0 missing
complemnumeric3 unique values
0 missing
vitaminnumeric9 unique values
0 missing
expandnumeric4 unique values
0 missing
calorinumeric7 unique values
0 missing
biopsinumeric5 unique values
0 missing
painumeric4 unique values
0 missing
homenumeric6 unique values
0 missing
healthinumeric5 unique values
0 missing
subnumeric3 unique values
0 missing
osmolarnumeric2 unique values
0 missing
readilinumeric3 unique values
0 missing
replicnumeric2 unique values
0 missing
febrilnumeric3 unique values
0 missing
recombinnumeric6 unique values
0 missing
methodologinumeric2 unique values
0 missing
vitalnumeric2 unique values
0 missing
concentrnumeric10 unique values
0 missing
multidisciplinarinumeric2 unique values
0 missing
reliablnumeric4 unique values
0 missing
cyclicnumeric3 unique values
0 missing
amnionnumeric3 unique values
0 missing
enrollnumeric3 unique values
0 missing
contextnumeric2 unique values
0 missing
describnumeric4 unique values
0 missing
disciplinnumeric2 unique values
0 missing
refernumeric4 unique values
0 missing
itemnumeric5 unique values
0 missing
seasonnumeric2 unique values
0 missing
fertilnumeric8 unique values
0 missing
twofoldnumeric2 unique values
0 missing
susceptnumeric3 unique values
0 missing
autolognumeric4 unique values
0 missing
coincidnumeric2 unique values
0 missing
amniotnumeric4 unique values
0 missing
analyznumeric3 unique values
0 missing
overalnumeric4 unique values
0 missing
paediatrnumeric3 unique values
0 missing
serotoninnumeric3 unique values
0 missing
predominantlinumeric3 unique values
0 missing
quicklinumeric2 unique values
0 missing
capacnumeric6 unique values
0 missing
expansnumeric4 unique values
0 missing
mitochondrinumeric4 unique values
0 missing
maneuvnumeric3 unique values
0 missing
intraopnumeric4 unique values
0 missing
glomerularnumeric7 unique values
0 missing
prenatnumeric5 unique values
0 missing
conductnumeric3 unique values
0 missing
typnumeric4 unique values
0 missing
remnantnumeric4 unique values
0 missing
hybridnumeric4 unique values
0 missing
preincubnumeric4 unique values
0 missing
odnumeric4 unique values
0 missing
weaklinumeric2 unique values
0 missing
postabsorptnumeric3 unique values
0 missing
returnnumeric4 unique values
0 missing
fortifinumeric3 unique values
0 missing
papnumeric4 unique values
0 missing
materinumeric4 unique values
0 missing
pentobarbitnumeric2 unique values
0 missing
suboptimnumeric2 unique values
0 missing
surgerinumeric6 unique values
0 missing
transfusnumeric3 unique values
0 missing
leukotriennumeric6 unique values
0 missing
extractnumeric4 unique values
0 missing
completnumeric4 unique values
0 missing
correspondnumeric3 unique values
0 missing
northnumeric3 unique values
0 missing
represnumeric3 unique values
0 missing
thinnumeric2 unique values
0 missing
parnumeric3 unique values
0 missing
cirrhosinumeric4 unique values
0 missing
kinetnumeric3 unique values
0 missing
sumnumeric2 unique values
0 missing
beliefnumeric2 unique values
0 missing
semennumeric8 unique values
0 missing
migratnumeric2 unique values
0 missing
establishnumeric4 unique values
0 missing
ohnumeric4 unique values
0 missing
habitnumeric3 unique values
0 missing
differnumeric5 unique values
0 missing
chromosomnumeric6 unique values
0 missing
matrixnumeric3 unique values
0 missing
chronicnumeric7 unique values
0 missing
pelvicnumeric2 unique values
0 missing
sympathetnumeric5 unique values
0 missing
resolvnumeric2 unique values
0 missing
photoreceptornumeric3 unique values
0 missing
fluoresceinnumeric3 unique values
0 missing
handlnumeric3 unique values
0 missing
reproducnumeric2 unique values
0 missing
complexnumeric3 unique values
0 missing
antinumeric6 unique values
0 missing
picturnumeric2 unique values
0 missing
metabolitnumeric7 unique values
0 missing
hypertensnumeric9 unique values
0 missing
percentilnumeric3 unique values
0 missing
maternnumeric8 unique values
0 missing
hardnumeric2 unique values
0 missing
consciounumeric3 unique values
0 missing
epitheliumnumeric3 unique values
0 missing
ontonumeric2 unique values
0 missing
angiographinumeric3 unique values
0 missing
disadvantagnumeric2 unique values
0 missing
parentnumeric7 unique values
0 missing
focunumeric5 unique values
0 missing
magnitudnumeric3 unique values
0 missing
postmenopausnumeric3 unique values
0 missing
oxidasnumeric4 unique values
0 missing
ingestnumeric8 unique values
0 missing
pediatrnumeric5 unique values
0 missing
citnumeric2 unique values
0 missing
transducnumeric2 unique values
0 missing
libitumnumeric5 unique values
0 missing
consistnumeric4 unique values
0 missing
illustrnumeric2 unique values
0 missing
mucosnumeric3 unique values
0 missing
falsenumeric4 unique values
0 missing
alternnumeric3 unique values
0 missing
outbreaknumeric2 unique values
0 missing
genernumeric6 unique values
0 missing
bornnumeric4 unique values
0 missing
contrastnumeric5 unique values
0 missing
corticosteroidnumeric3 unique values
0 missing
cognitnumeric4 unique values
0 missing
consecutnumeric3 unique values
0 missing
believnumeric2 unique values
0 missing
cumulnumeric3 unique values
0 missing
rectalnumeric2 unique values
0 missing
percentnumeric8 unique values
0 missing
hypoglycemianumeric4 unique values
0 missing
breechnumeric5 unique values
0 missing
trendnumeric3 unique values
0 missing
explainnumeric5 unique values
0 missing
learnnumeric3 unique values
0 missing
instancnumeric2 unique values
0 missing
androgennumeric2 unique values
0 missing
tubulnumeric3 unique values
0 missing
constructnumeric2 unique values
0 missing
isocalornumeric3 unique values
0 missing
relationshipnumeric4 unique values
0 missing
primiparnumeric4 unique values
0 missing
jamanumeric2 unique values
0 missing
detrimentnumeric2 unique values
0 missing
councilnumeric2 unique values
0 missing
uncertaintinumeric2 unique values
0 missing
genetnumeric4 unique values
0 missing
baselinnumeric5 unique values
0 missing
fecenumeric3 unique values
0 missing
inactivnumeric3 unique values
0 missing
oocytnumeric7 unique values
0 missing
quantitnumeric4 unique values
0 missing
eyenumeric8 unique values
0 missing
cdnanumeric3 unique values
0 missing
vitrectominumeric3 unique values
0 missing
ethnicnumeric3 unique values
0 missing
morphometrnumeric3 unique values
0 missing
cytoplasmnumeric5 unique values
0 missing
nuclearnumeric5 unique values
0 missing
lipoproteinnumeric8 unique values
0 missing
dementianumeric5 unique values
0 missing
birthnumeric10 unique values
0 missing
restrictnumeric7 unique values
0 missing
societinumeric4 unique values
0 missing
studentnumeric8 unique values
0 missing
starchnumeric5 unique values
0 missing
formulanumeric5 unique values
0 missing
offsetnumeric2 unique values
0 missing
instillnumeric3 unique values
0 missing
pgnumeric7 unique values
0 missing
packnumeric5 unique values
0 missing
parallelnumeric2 unique values
0 missing
abilnumeric5 unique values
0 missing
strongestnumeric2 unique values
0 missing
ovariannumeric3 unique values
0 missing
lightnumeric3 unique values
0 missing
psychiatrnumeric5 unique values
0 missing
insteadnumeric2 unique values
0 missing
heterosexunumeric2 unique values
0 missing
funduscopnumeric2 unique values
0 missing
tailnumeric3 unique values
0 missing
deoxyribonuclnumeric3 unique values
0 missing
phnumeric6 unique values
0 missing
uncertainnumeric2 unique values
0 missing
highlightnumeric3 unique values
0 missing
barriernumeric5 unique values
0 missing
crossnumeric5 unique values
0 missing
ketonumeric6 unique values
0 missing
concurrnumeric2 unique values
0 missing
urolognumeric4 unique values
0 missing
predictnumeric6 unique values
0 missing
unexplainnumeric4 unique values
0 missing
unnecessarinumeric3 unique values
0 missing
curriculumnumeric6 unique values
0 missing
infancnumeric3 unique values
0 missing
unlessnumeric2 unique values
0 missing
polymorphnumeric4 unique values
0 missing
endoscopnumeric4 unique values
0 missing
uncommonnumeric2 unique values
0 missing
transcriptnumeric5 unique values
0 missing
friendnumeric2 unique values
0 missing
hemodynamnumeric6 unique values
0 missing
clearancnumeric6 unique values
0 missing

107 properties

1050
Number of instances (rows) of the dataset.
3239
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.
3238
Number of numeric attributes.
1
Number of nominal attributes.
Maximum entropy among attributes.
4.85
Minimum kurtosis among attributes of the numeric type.
0.01
Second quartile (Median) of means among attributes of the numeric type.
0.91
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.6
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
1025.83
Maximum kurtosis among attributes of the numeric type.
0
Minimum of means among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.32
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.74
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
0.13
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
1.41
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
15.73
Second quartile (Median) of skewness among attributes of the numeric type.
0.64
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
3.08
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 binary attributes.
0.15
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.63
Area Under the ROC Curve 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.
1.91
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
0.65
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.26
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.85
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
31.87
Maximum skewness among attributes of the numeric type.
0.05
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
407.48
Third quartile of kurtosis among attributes of the numeric type.
0.29
Average class difference between consecutive instances.
0.63
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.3
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
2.86
Maximum standard deviation of attributes of the numeric type.
4.95
Percentage of instances belonging to the least frequent class.
99.97
Percentage of numeric attributes.
0.03
Third quartile of means among attributes of the numeric type.
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
0.65
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.67
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Average entropy of the attributes.
52
Number 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.
0.28
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
0.26
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.85
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
302.56
Mean kurtosis among attributes of the numeric type.
0.92
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of entropy among attributes.
19.2
Third quartile of skewness among attributes of the numeric type.
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
0.63
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.3
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0.03
Mean of means among attributes of the numeric type.
0.31
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
128.69
First quartile of kurtosis among attributes of the numeric type.
0.27
Third quartile of standard deviation of attributes of the numeric type.
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
0.65
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.67
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Average mutual information between the nominal attributes and the target attribute.
0.65
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.01
First quartile of means among attributes of the numeric type.
0.91
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
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
0.26
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.85
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.
First quartile of mutual information between the nominal attributes and the target attribute.
0.32
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
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
0
Standard deviation of the number of distinct values among attributes of the nominal type.
0.3
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.
10.68
First quartile of skewness among attributes of the numeric type.
0.64
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
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
0.53
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.67
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
15.54
Mean skewness among attributes of the numeric type.
0.09
First quartile of standard deviation of attributes of the numeric type.
0.91
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
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
0.85
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
15.71
Percentage of instances belonging to the most frequent class.
0.22
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
0.32
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
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
0.07
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
165
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
258.74
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.64
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
3.2
Entropy of the target attribute values.

52 tasks

289 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: 33% Holdout set - 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
35 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