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tr11.wc

active Sparse_ARFF Publicly available Visibility: public Uploaded 28-09-2014 by Joaquin Vanschoren
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6430 features

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debat	numeric	8 unique values 0 missing
collater	numeric	2 unique values 0 missing
throughout	numeric	8 unique values 0 missing
oman	numeric	3 unique values 0 missing
vicin	numeric	5 unique values 0 missing
laboratori	numeric	9 unique values 0 missing
amplifi	numeric	4 unique values 0 missing
prepar	numeric	13 unique values 0 missing
settle	numeric	3 unique values 0 missing
izvestiya	numeric	5 unique values 0 missing
presidium	numeric	4 unique values 0 missing
comrad	numeric	4 unique values 0 missing
tidal	numeric	2 unique values 0 missing
northwest	numeric	5 unique values 0 missing
plantat	numeric	3 unique values 0 missing
dead	numeric	5 unique values 0 missing
plutonium	numeric	9 unique values 0 missing
liepaja	numeric	3 unique values 0 missing
activist	numeric	4 unique values 0 missing
eximbank	numeric	2 unique values 0 missing
extremist	numeric	3 unique values 0 missing
advertis	numeric	5 unique values 0 missing
meant	numeric	2 unique values 0 missing
capac	numeric	15 unique values 0 missing
motor	numeric	15 unique values 0 missing
affluent	numeric	3 unique values 0 missing
proof	numeric	3 unique values 0 missing
concret	numeric	6 unique values 0 missing
secretari	numeric	7 unique values 0 missing
philippin	numeric	6 unique values 0 missing
mandat	numeric	5 unique values 0 missing
custom	numeric	10 unique values 0 missing
fed	numeric	2 unique values 0 missing
palestin	numeric	2 unique values 0 missing
sharpli	numeric	5 unique values 0 missing
ideologi	numeric	3 unique values 0 missing
foreshadow	numeric	2 unique values 0 missing
burial	numeric	8 unique values 0 missing
clarif	numeric	3 unique values 0 missing
english	numeric	10 unique values 0 missing
pend	numeric	2 unique values 0 missing
width	numeric	3 unique values 0 missing
spill	numeric	8 unique values 0 missing
infect	numeric	6 unique values 0 missing
monoxid	numeric	4 unique values 0 missing
jet	numeric	3 unique values 0 missing
forecast	numeric	5 unique values 0 missing
worn	numeric	3 unique values 0 missing
automot	numeric	4 unique values 0 missing
correspond	numeric	7 unique values 0 missing
contrari	numeric	4 unique values 0 missing
extent	numeric	5 unique values 0 missing
invit	numeric	8 unique values 0 missing
scatter	numeric	2 unique values 0 missing
governor	numeric	5 unique values 0 missing
advic	numeric	3 unique values 0 missing
allot	numeric	3 unique values 0 missing
hebei	numeric	6 unique values 0 missing
cypru	numeric	3 unique values 0 missing
conserv	numeric	8 unique values 0 missing
portugues	numeric	4 unique values 0 missing
therein	numeric	3 unique values 0 missing
print	numeric	6 unique values 0 missing
yerevan	numeric	3 unique values 0 missing
alphabet	numeric	3 unique values 0 missing
daili	numeric	10 unique values 0 missing
giang	numeric	4 unique values 0 missing
rossiyskiy	numeric	4 unique values 0 missing
paz	numeric	3 unique values 0 missing
kherson	numeric	4 unique values 0 missing
dissolut	numeric	5 unique values 0 missing
juppe	numeric	5 unique values 0 missing
kozyrev	numeric	5 unique values 0 missing
algerian	numeric	6 unique values 0 missing
fujii	numeric	4 unique values 0 missing
crystal	numeric	5 unique values 0 missing
inhibit	numeric	2 unique values 0 missing
tourist	numeric	9 unique values 0 missing
beforehand	numeric	3 unique values 0 missing
fig	numeric	6 unique values 0 missing
industri	numeric	36 unique values 0 missing
mekong	numeric	5 unique values 0 missing
ido	numeric	4 unique values 0 missing
lien	numeric	4 unique values 0 missing
liquefi	numeric	4 unique values 0 missing
gold	numeric	9 unique values 0 missing
subhead	numeric	2 unique values 0 missing
mikhaylov	numeric	4 unique values 0 missing
admiss	numeric	4 unique values 0 missing
vest	numeric	2 unique values 0 missing
flower	numeric	3 unique values 0 missing
candidaci	numeric	4 unique values 0 missing
ignition	numeric	3 unique values 0 missing
cosmic	numeric	3 unique values 0 missing
desertif	numeric	6 unique values 0 missing
neck	numeric	2 unique values 0 missing
sampl	numeric	2 unique values 0 missing
petersburg	numeric	7 unique values 0 missing
yourself	numeric	2 unique values 0 missing
nil	numeric	2 unique values 0 missing
foundat	numeric	10 unique values 0 missing
unidentifi	numeric	3 unique values 0 missing
couple	numeric	2 unique values 0 missing
frankfurt	numeric	4 unique values 0 missing
minimum	numeric	5 unique values 0 missing
southeast	numeric	12 unique values 0 missing
trial	numeric	5 unique values 0 missing
heate	numeric	12 unique values 0 missing
fe	numeric	3 unique values 0 missing
portion	numeric	4 unique values 0 missing
institut	numeric	23 unique values 0 missing
pour	numeric	4 unique values 0 missing
fragment	numeric	4 unique values 0 missing
silesia	numeric	3 unique values 0 missing
intermedi	numeric	3 unique values 0 missing
alien	numeric	3 unique values 0 missing
0	numeric	36 unique values 0 missing
auxiliari	numeric	3 unique values 0 missing
seismic	numeric	4 unique values 0 missing
tarasov	numeric	3 unique values 0 missing
rifle	numeric	3 unique values 0 missing
polym	numeric	5 unique values 0 missing
deck	numeric	3 unique values 0 missing
tragedi	numeric	3 unique values 0 missing
nowadai	numeric	2 unique values 0 missing
scrap	numeric	7 unique values 0 missing
quiet	numeric	2 unique values 0 missing
human	numeric	12 unique values 0 missing
environment	numeric	25 unique values 0 missing
advisori	numeric	5 unique values 0 missing
chines	numeric	16 unique values 0 missing
presid	numeric	16 unique values 0 missing
struggle	numeric	6 unique values 0 missing
atr	numeric	4 unique values 0 missing
outlai	numeric	3 unique values 0 missing
deepli	numeric	4 unique values 0 missing
biolog	numeric	9 unique values 0 missing
healthi	numeric	7 unique values 0 missing
zero	numeric	3 unique values 0 missing
harmoni	numeric	3 unique values 0 missing
hangar	numeric	3 unique values 0 missing
british	numeric	8 unique values 0 missing
fu	numeric	2 unique values 0 missing
nineti	numeric	3 unique values 0 missing
clinic	numeric	6 unique values 0 missing
protector	numeric	3 unique values 0 missing
cod	numeric	4 unique values 0 missing
handelsblat	numeric	4 unique values 0 missing
irrespons	numeric	3 unique values 0 missing
renegoti	numeric	4 unique values 0 missing
renault	numeric	5 unique values 0 missing
cast	numeric	4 unique values 0 missing
specialist	numeric	10 unique values 0 missing
frankli	numeric	2 unique values 0 missing
negoti	numeric	13 unique values 0 missing
mean	numeric	13 unique values 0 missing
transpar	numeric	5 unique values 0 missing
polyethylen	numeric	2 unique values 0 missing
diversif	numeric	2 unique values 0 missing
yang	numeric	4 unique values 0 missing
professor	numeric	6 unique values 0 missing
allevi	numeric	4 unique values 0 missing
chu	numeric	4 unique values 0 missing
doctor	numeric	6 unique values 0 missing
crise	numeric	3 unique values 0 missing
epoxi	numeric	4 unique values 0 missing
metalwork	numeric	3 unique values 0 missing
writer	numeric	4 unique values 0 missing
halla	numeric	4 unique values 0 missing
scenic	numeric	2 unique values 0 missing
ostrov	numeric	4 unique values 0 missing
ultraviolet	numeric	4 unique values 0 missing
bureaucrat	numeric	4 unique values 0 missing
ourselv	numeric	3 unique values 0 missing
vulner	numeric	3 unique values 0 missing
odor	numeric	3 unique values 0 missing
thirti	numeric	2 unique values 0 missing
reliabl	numeric	6 unique values 0 missing
stabil	numeric	9 unique values 0 missing
septemb	numeric	10 unique values 0 missing
fit	numeric	3 unique values 0 missing
begun	numeric	8 unique values 0 missing
nhate	numeric	4 unique values 0 missing
zhao	numeric	3 unique values 0 missing
thoi	numeric	7 unique values 0 missing
shar	numeric	5 unique values 0 missing
ratif	numeric	4 unique values 0 missing
constraint	numeric	2 unique values 0 missing
merchandis	numeric	5 unique values 0 missing
hon	numeric	3 unique values 0 missing
undecid	numeric	4 unique values 0 missing
purchas	numeric	12 unique values 0 missing
bohai	numeric	2 unique values 0 missing
ninh	numeric	4 unique values 0 missing
canari	numeric	2 unique values 0 missing
ismail	numeric	2 unique values 0 missing
khi	numeric	4 unique values 0 missing
novosibirsk	numeric	4 unique values 0 missing
countrymen	numeric	3 unique values 0 missing
golden	numeric	3 unique values 0 missing
tsutomu	numeric	3 unique values 0 missing
stronger	numeric	5 unique values 0 missing
fifteen	numeric	2 unique values 0 missing
farmer	numeric	8 unique values 0 missing
lack	numeric	11 unique values 0 missing
western	numeric	10 unique values 0 missing
pai	numeric	13 unique values 0 missing
suzhou	numeric	4 unique values 0 missing
extraordinari	numeric	6 unique values 0 missing
kia	numeric	5 unique values 0 missing
coordin	numeric	12 unique values 0 missing
macao	numeric	5 unique values 0 missing
railwai	numeric	6 unique values 0 missing
electricit	numeric	2 unique values 0 missing
idle	numeric	2 unique values 0 missing
buffer	numeric	3 unique values 0 missing
justic	numeric	6 unique values 0 missing
southwestern	numeric	3 unique values 0 missing
angle	numeric	3 unique values 0 missing
fusion	numeric	3 unique values 0 missing
forbidden	numeric	2 unique values 0 missing
textbook	numeric	3 unique values 0 missing
armenian	numeric	5 unique values 0 missing
continent	numeric	4 unique values 0 missing
media	numeric	10 unique values 0 missing
tarif	numeric	10 unique values 0 missing
kurchatov	numeric	2 unique values 0 missing
devot	numeric	6 unique values 0 missing
centerpiec	numeric	2 unique values 0 missing
kumagai	numeric	3 unique values 0 missing
jointli	numeric	10 unique values 0 missing
competitor	numeric	5 unique values 0 missing
specialti	numeric	3 unique values 0 missing
mine	numeric	9 unique values 0 missing
guangdong	numeric	8 unique values 0 missing
hiroshi	numeric	2 unique values 0 missing
prolifer	numeric	3 unique values 0 missing
rude	numeric	3 unique values 0 missing
vcr	numeric	5 unique values 0 missing
peninsula	numeric	6 unique values 0 missing
koptev	numeric	4 unique values 0 missing
affair	numeric	10 unique values 0 missing
arianespac	numeric	3 unique values 0 missing
nozzle	numeric	2 unique values 0 missing
recur	numeric	3 unique values 0 missing
kidnei	numeric	2 unique values 0 missing
threshold	numeric	5 unique values 0 missing
classif	numeric	4 unique values 0 missing
csce	numeric	3 unique values 0 missing
strain	numeric	4 unique values 0 missing
tep	numeric	2 unique values 0 missing
jingji	numeric	5 unique values 0 missing
iron	numeric	9 unique values 0 missing
bulletin	numeric	4 unique values 0 missing
commission	numeric	4 unique values 0 missing
south	numeric	19 unique values 0 missing
unoffici	numeric	2 unique values 0 missing
tdx	numeric	3 unique values 0 missing
flavor	numeric	3 unique values 0 missing
sharp	numeric	5 unique values 0 missing
degree	numeric	9 unique values 0 missing
conceptu	numeric	3 unique values 0 missing
emit	numeric	4 unique values 0 missing
yong	numeric	6 unique values 0 missing
repetit	numeric	2 unique values 0 missing
jurid	numeric	4 unique values 0 missing
march	numeric	19 unique values 0 missing
meteorolog	numeric	5 unique values 0 missing
analyt	numeric	4 unique values 0 missing
m	numeric	3 unique values 0 missing
estonian	numeric	4 unique values 0 missing
electrotechn	numeric	3 unique values 0 missing
absenc	numeric	4 unique values 0 missing
excerpt	numeric	3 unique values 0 missing
spend	numeric	7 unique values 0 missing
stimul	numeric	5 unique values 0 missing
formerli	numeric	3 unique values 0 missing
lin	numeric	4 unique values 0 missing
taiwan	numeric	13 unique values 0 missing
signal	numeric	7 unique values 0 missing
understand	numeric	9 unique values 0 missing
workstat	numeric	5 unique values 0 missing
presum	numeric	3 unique values 0 missing
min	numeric	12 unique values 0 missing
summar	numeric	4 unique values 0 missing
six	numeric	14 unique values 0 missing
accommod	numeric	4 unique values 0 missing
asean	numeric	4 unique values 0 missing
plot	numeric	3 unique values 0 missing
naewoe	numeric	2 unique values 0 missing
riga	numeric	5 unique values 0 missing
turnov	numeric	6 unique values 0 missing
mountain	numeric	7 unique values 0 missing
tackle	numeric	4 unique values 0 missing
envoi	numeric	3 unique values 0 missing
nursultan	numeric	2 unique values 0 missing
scan	numeric	2 unique values 0 missing
spoil	numeric	3 unique values 0 missing
taxpay	numeric	2 unique values 0 missing
explor	numeric	9 unique values 0 missing
center	numeric	21 unique values 0 missing
jeopard	numeric	4 unique values 0 missing
vital	numeric	3 unique values 0 missing
pao	numeric	9 unique values 0 missing
song	numeric	4 unique values 0 missing
enterpris	numeric	25 unique values 0 missing
chain	numeric	8 unique values 0 missing
bubble	numeric	3 unique values 0 missing
qatar	numeric	2 unique values 0 missing
care	numeric	5 unique values 0 missing
advanc	numeric	17 unique values 0 missing
ratifi	numeric	5 unique values 0 missing
cluster	numeric	3 unique values 0 missing
diminish	numeric	3 unique values 0 missing
contour	numeric	3 unique values 0 missing
detach	numeric	3 unique values 0 missing
bolt	numeric	2 unique values 0 missing
headlin	numeric	3 unique values 0 missing
night	numeric	3 unique values 0 missing
bitter	numeric	2 unique values 0 missing
kazakh	numeric	7 unique values 0 missing
discrep	numeric	3 unique values 0 missing
hang	numeric	2 unique values 0 missing
hitherto	numeric	3 unique values 0 missing
respond	numeric	10 unique values 0 missing
overli	numeric	2 unique values 0 missing
catv	numeric	3 unique values 0 missing
nuclear	numeric	28 unique values 0 missing
remit	numeric	2 unique values 0 missing
alcohol	numeric	3 unique values 0 missing
yield	numeric	7 unique values 0 missing
radic	numeric	8 unique values 0 missing
easili	numeric	4 unique values 0 missing
petrochem	numeric	9 unique values 0 missing
dissemin	numeric	5 unique values 0 missing
collaps	numeric	5 unique values 0 missing

Show first 100 features

107 properties

NumberOfInstances

414

Number of instances (rows) of the dataset.

NumberOfFeatures

6430

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

6429

Number of numeric attributes.

NumberOfSymbolicFeatures

Number of nominal attributes.

Quartile2KurtosisOfNumericAtts

134.64

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

REPTreeDepth2Kappa

0.72

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

ClassEntropy

2.7

Entropy of the target attribute values.

kNN1NKappa

0.21

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

MajorityClassSize

132

Number of instances belonging to the most frequent class.

MinAttributeEntropy

Minimal entropy among attributes.

Quartile2MeansOfNumericAtts

0.04

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

REPTreeDepth3AUC

0.92

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3

DecisionStumpAUC

0.69

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

MaxAttributeEntropy

Maximum entropy among attributes.

MinKurtosisOfNumericAtts

-1.9

Minimum kurtosis among attributes of the numeric type.

Quartile2MutualInformation

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

REPTreeDepth3ErrRate

0.23

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

DecisionStumpErrRate

0.56

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

MaxKurtosisOfNumericAtts

413.92

Maximum kurtosis among attributes of the numeric type.

MinMeansOfNumericAtts

0.01

Minimum of means among attributes of the numeric type.

Quartile2SkewnessOfNumericAtts

11.49

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

REPTreeDepth3Kappa

0.72

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

DecisionStumpKappa

0.22

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

MaxMeansOfNumericAtts

20.14

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

0.33

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

RandomTreeDepth1AUC

0.67

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

Dimensionality

15.53

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

-0.59

Minimum skewness among attributes of the numeric type.

PercentageOfMissingValues

Percentage of missing values.

Quartile3KurtosisOfNumericAtts

204.71

Third quartile of kurtosis among attributes of the numeric type.

AutoCorrelation

0.2

Average class difference between consecutive instances.

RandomTreeDepth1Kappa

0.34

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

J48.00001.AUC

0.82

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

MaxSkewnessOfNumericAtts

20.34

Maximum skewness among attributes of the numeric type.

MinStdDevOfNumericAtts

Minimum standard deviation of attributes of the numeric type.

PercentageOfNumericFeatures

99.98

Percentage of numeric attributes.

Quartile3MeansOfNumericAtts

0.12

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

0.67

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

J48.00001.ErrRate

0.3

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

MaxStdDevOfNumericAtts

155.38

Maximum standard deviation of attributes of the numeric type.

MinorityClassPercentage

1.45

Percentage of instances belonging to the least frequent class.

PercentageOfSymbolicFeatures

0.02

Percentage of nominal attributes.

Quartile3MutualInformation

Third quartile of mutual information between the nominal attributes and the target attribute.

CfsSubsetEval_DecisionStumpErrRate

0.22

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

0.61

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

13.79

Third quartile of skewness among attributes of the numeric type.

CfsSubsetEval_DecisionStumpKappa

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

RandomTreeDepth2Kappa

0.34

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

J48.0001.AUC

0.82

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

MeanKurtosisOfNumericAtts

157.54

Mean kurtosis among attributes of the numeric type.

NaiveBayesAUC

0.81

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

Quartile1KurtosisOfNumericAtts

80.66

First quartile of kurtosis among attributes of the numeric type.

Quartile3StdDevOfNumericAtts

0.82

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

0.67

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

J48.0001.ErrRate

0.3

Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001

MeanMeansOfNumericAtts

0.16

Mean of means among attributes of the numeric type.

NaiveBayesErrRate

0.47

Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes

Quartile1MeansOfNumericAtts

0.02

First quartile of means among attributes of the numeric type.

REPTreeDepth1AUC

0.92

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

CfsSubsetEval_NaiveBayesErrRate

0.22

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

0.61

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

0.45

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

0.23

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

CfsSubsetEval_NaiveBayesKappa

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

RandomTreeDepth3Kappa

0.34

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

J48.001.AUC

0.82

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

8.67

First quartile of skewness among attributes of the numeric type.

REPTreeDepth1Kappa

0.72

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

0.3

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

MeanNominalAttDistinctValues

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

Quartile1StdDevOfNumericAtts

0.16

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

REPTreeDepth2AUC

0.92

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

CfsSubsetEval_kNN1NErrRate

0.22

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

0.6

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

J48.001.Kappa

0.61

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

MeanSkewnessOfNumericAtts

11.45

Mean skewness among attributes of the numeric type.

Quartile2AttributeEntropy

Second quartile (Median) of entropy among attributes.

REPTreeDepth2ErrRate

0.23

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

CfsSubsetEval_kNN1NKappa

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

kNN1NErrRate

0.6

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

MajorityClassPercentage

31.88

Percentage of instances belonging to the most frequent class.

MeanStdDevOfNumericAtts

1.07

Mean standard deviation of attributes of the numeric type.

Show all 107 properties

21 tasks

Supervised Classification on tr11.wc

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

Supervised Classification on tr11.wc

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

Supervised Regression on tr11.wc

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

Supervised Regression on tr11.wc

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

Supervised Regression on tr11.wc

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

Supervised Regression on tr11.wc

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

Supervised Regression on tr11.wc

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

Supervised Regression on tr11.wc

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

Supervised Regression on tr11.wc

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

Supervised Data Stream Classification on tr11.wc

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

Clustering on tr11.wc