Data
mfeat-factors

mfeat-factors

active ARFF Publicly available Visibility: public Uploaded 04-10-2014 by Joaquin Vanschoren
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Author: Source: Unknown - Date unknown Please cite: Binarized version of the original data set (see version 1). The multi-class target feature is converted to a two-class nominal target feature by re-labeling the majority class as positive ('P') and all others as negative ('N'). Originally converted by Quan Sun.

217 features

binaryClass (target)nominal2 unique values
0 missing
att1numeric390 unique values
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att2numeric446 unique values
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att3numeric541 unique values
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att4numeric440 unique values
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att5numeric252 unique values
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att6numeric419 unique values
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att7numeric43 unique values
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att8numeric39 unique values
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att9numeric40 unique values
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att10numeric18 unique values
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att11numeric19 unique values
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att12numeric18 unique values
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att13numeric336 unique values
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att14numeric420 unique values
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att15numeric421 unique values
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att16numeric351 unique values
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att17numeric257 unique values
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att18numeric405 unique values
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att19numeric42 unique values
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att20numeric41 unique values
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att21numeric41 unique values
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att26numeric439 unique values
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att37numeric402 unique values
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att42numeric364 unique values
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att44numeric39 unique values
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att45numeric44 unique values
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att47numeric22 unique values
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att48numeric23 unique values
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att49numeric300 unique values
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att52numeric413 unique values
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att53numeric375 unique values
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att54numeric367 unique values
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att56numeric40 unique values
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att57numeric44 unique values
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att58numeric24 unique values
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att61numeric302 unique values
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att62numeric348 unique values
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att63numeric464 unique values
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att65numeric449 unique values
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att66numeric383 unique values
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att67numeric41 unique values
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att68numeric38 unique values
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att69numeric43 unique values
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att71numeric20 unique values
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att72numeric25 unique values
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att73numeric304 unique values
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att74numeric361 unique values
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att75numeric435 unique values
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att76numeric395 unique values
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att77numeric313 unique values
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att78numeric432 unique values
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att80numeric40 unique values
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att81numeric41 unique values
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att82numeric25 unique values
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att85numeric301 unique values
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att86numeric460 unique values
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att87numeric427 unique values
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att88numeric448 unique values
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att96numeric23 unique values
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att97numeric473 unique values
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att98numeric390 unique values
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att99numeric352 unique values
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att100numeric494 unique values
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att101numeric268 unique values
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att102numeric394 unique values
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att106numeric23 unique values
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att108numeric20 unique values
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att109numeric450 unique values
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att110numeric342 unique values
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att111numeric590 unique values
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att115numeric44 unique values
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att116numeric30 unique values
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att117numeric41 unique values
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att118numeric18 unique values
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att119numeric23 unique values
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att120numeric24 unique values
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att121numeric279 unique values
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att122numeric341 unique values
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att126numeric374 unique values
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att128numeric32 unique values
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att129numeric45 unique values
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att131numeric19 unique values
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att132numeric26 unique values
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att133numeric364 unique values
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att134numeric349 unique values
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att135numeric590 unique values
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att136numeric441 unique values
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att137numeric335 unique values
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att138numeric326 unique values
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att139numeric37 unique values
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att140numeric35 unique values
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att141numeric35 unique values
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att142numeric23 unique values
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att143numeric19 unique values
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att144numeric23 unique values
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att145numeric278 unique values
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att146numeric434 unique values
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att147numeric501 unique values
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att148numeric492 unique values
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att149numeric302 unique values
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att150numeric355 unique values
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att151numeric37 unique values
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att152numeric32 unique values
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att153numeric35 unique values
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att156numeric25 unique values
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att157numeric379 unique values
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att158numeric398 unique values
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att159numeric357 unique values
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att160numeric403 unique values
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att161numeric327 unique values
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att162numeric449 unique values
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att163numeric44 unique values
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att164numeric34 unique values
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att165numeric46 unique values
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att166numeric25 unique values
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att167numeric22 unique values
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att168numeric19 unique values
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att169numeric359 unique values
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att170numeric394 unique values
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att171numeric435 unique values
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att172numeric314 unique values
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att173numeric454 unique values
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att174numeric381 unique values
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att175numeric44 unique values
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att176numeric39 unique values
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att177numeric45 unique values
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att178numeric18 unique values
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att179numeric22 unique values
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att180numeric26 unique values
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att181numeric499 unique values
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att182numeric402 unique values
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att183numeric540 unique values
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att184numeric416 unique values
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att185numeric460 unique values
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att186numeric434 unique values
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att187numeric43 unique values
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att188numeric43 unique values
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att189numeric45 unique values
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att190numeric18 unique values
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att191numeric25 unique values
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att192numeric25 unique values
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att193numeric445 unique values
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att194numeric517 unique values
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att195numeric474 unique values
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att196numeric458 unique values
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att197numeric255 unique values
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att198numeric463 unique values
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att199numeric46 unique values
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att200numeric41 unique values
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att201numeric44 unique values
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att202numeric25 unique values
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att203numeric25 unique values
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att204numeric19 unique values
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att205numeric303 unique values
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att206numeric330 unique values
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att207numeric550 unique values
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att208numeric472 unique values
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att209numeric292 unique values
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att210numeric391 unique values
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att211numeric30 unique values
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att212numeric38 unique values
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att213numeric36 unique values
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att214numeric15 unique values
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att215numeric15 unique values
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att216numeric24 unique values
0 missing
Show first 100 features

107 properties

NumberOfInstances
2000
Number of instances (rows) of the dataset.
NumberOfFeatures
217
Number of attributes (columns) of the dataset.
NumberOfClasses
2
Number of distinct values of the target attribute (if it is nominal).
NumberOfMissingValues
0
Number of missing values in the dataset.
NumberOfInstancesWithMissingValues
0
Number of instances with at least one value missing.
NumberOfNumericFeatures
216
Number of numeric attributes.
NumberOfSymbolicFeatures
1
Number of nominal attributes.
REPTreeDepth3Kappa
0.93
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
DecisionStumpKappa
0.89
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
MaxMeansOfNumericAtts
1141.57
Maximum of means among attributes of the numeric type.
MinMutualInformation
Minimal mutual information between the nominal attributes and the target attribute.
Quartile2SkewnessOfNumericAtts
-0.01
Second quartile (Median) of skewness among attributes of the numeric type.
RandomTreeDepth1AUC
0.96
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
Dimensionality
0.11
Number of attributes divided by the number of instances.
MaxMutualInformation
Maximum mutual information between the nominal attributes and the target attribute.
MinNominalAttDistinctValues
2
The minimal number of distinct values among attributes of the nominal type.
PercentageOfBinaryFeatures
0.46
Percentage of binary attributes.
Quartile2StdDevOfNumericAtts
30.29
Second quartile (Median) of standard deviation of attributes of the numeric type.
RandomTreeDepth1ErrRate
0.02
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
2
The maximum number of distinct values among attributes of the nominal type.
MinSkewnessOfNumericAtts
-1.07
Minimum skewness among attributes of the numeric type.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
Quartile3AttributeEntropy
Third quartile of entropy among attributes.
RandomTreeDepth1Kappa
0.9
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
J48.00001.AUC
0.98
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
MaxSkewnessOfNumericAtts
0.86
Maximum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
1.99
Minimum standard deviation of attributes of the numeric type.
PercentageOfMissingValues
0
Percentage of missing values.
Quartile3KurtosisOfNumericAtts
0.01
Third quartile of kurtosis among attributes of the numeric type.
AutoCorrelation
1
Average class difference between consecutive instances.
RandomTreeDepth2AUC
0.96
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
J48.00001.ErrRate
0.01
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
MaxStdDevOfNumericAtts
153.51
Maximum standard deviation of attributes of the numeric type.
MinorityClassPercentage
10
Percentage of instances belonging to the least frequent class.
PercentageOfNumericFeatures
99.54
Percentage of numeric attributes.
Quartile3MeansOfNumericAtts
684.5
Third quartile of means among attributes of the numeric type.
CfsSubsetEval_DecisionStumpAUC
0.96
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
RandomTreeDepth2ErrRate
0.02
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
J48.00001.Kappa
0.94
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
MeanAttributeEntropy
Average entropy of the attributes.
MinorityClassSize
200
Number of instances belonging to the least frequent class.
PercentageOfSymbolicFeatures
0.46
Percentage of nominal attributes.
Quartile3MutualInformation
Third quartile of mutual information between the nominal attributes and the target attribute.
CfsSubsetEval_DecisionStumpErrRate
0.01
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
RandomTreeDepth2Kappa
0.9
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
J48.0001.AUC
0.98
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
MeanKurtosisOfNumericAtts
-0.32
Mean kurtosis among attributes of the numeric type.
NaiveBayesAUC
0.98
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
Quartile1AttributeEntropy
First quartile of entropy among attributes.
Quartile3SkewnessOfNumericAtts
0.37
Third quartile of skewness among attributes of the numeric type.
CfsSubsetEval_DecisionStumpKappa
0.93
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
RandomTreeDepth3AUC
0.96
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
J48.0001.ErrRate
0.01
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
MeanMeansOfNumericAtts
318.27
Mean of means among attributes of the numeric type.
NaiveBayesErrRate
0.05
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
Quartile1KurtosisOfNumericAtts
-0.7
First quartile of kurtosis among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
91.6
Third quartile of standard deviation of attributes of the numeric type.
CfsSubsetEval_NaiveBayesAUC
0.96
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
RandomTreeDepth3ErrRate
0.02
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
J48.0001.Kappa
0.94
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
0.78
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
Quartile1MeansOfNumericAtts
14.12
First quartile of means among attributes of the numeric type.
REPTreeDepth1AUC
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
CfsSubsetEval_NaiveBayesErrRate
0.01
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
RandomTreeDepth3Kappa
0.9
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
J48.001.AUC
0.98
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
1
Number of binary attributes.
Quartile1MutualInformation
First quartile of mutual information between the nominal attributes and the target attribute.
REPTreeDepth1ErrRate
0.01
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
CfsSubsetEval_NaiveBayesKappa
0.93
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
CfsSubsetEval_kNN1NAUC
0.96
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
0
Standard deviation of the number of distinct values among attributes of the nominal type.
J48.001.ErrRate
0.01
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
MeanNominalAttDistinctValues
2
Average number of distinct values among the attributes of the nominal type.
Quartile1SkewnessOfNumericAtts
-0.22
First quartile of skewness among attributes of the numeric type.
REPTreeDepth1Kappa
0.93
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
CfsSubsetEval_kNN1NErrRate
0.01
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
0.99
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
J48.001.Kappa
0.94
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
MeanSkewnessOfNumericAtts
0.03
Mean skewness among attributes of the numeric type.
Quartile1StdDevOfNumericAtts
5.54
First quartile of standard deviation of attributes of the numeric type.
REPTreeDepth2AUC
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
CfsSubsetEval_kNN1NKappa
0.93
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
0.01
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
MajorityClassPercentage
90
Percentage of instances belonging to the most frequent class.
MeanStdDevOfNumericAtts
49.58
Mean standard deviation of attributes of the numeric type.
Quartile2AttributeEntropy
Second quartile (Median) of entropy among attributes.
REPTreeDepth2ErrRate
0.01
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
ClassEntropy
0.47
Entropy of the target attribute values.
kNN1NKappa
0.96
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
MajorityClassSize
1800
Number of instances belonging to the most frequent class.
MinAttributeEntropy
Minimal entropy among attributes.
Quartile2KurtosisOfNumericAtts
-0.4
Second quartile (Median) of kurtosis among attributes of the numeric type.
REPTreeDepth2Kappa
0.93
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth3AUC
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
DecisionStumpAUC
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
MaxAttributeEntropy
Maximum entropy among attributes.
MinKurtosisOfNumericAtts
-1.39
Minimum kurtosis among attributes of the numeric type.
Quartile2MeansOfNumericAtts
146.48
Second quartile (Median) of means among attributes of the numeric type.
REPTreeDepth3ErrRate
0.01
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
DecisionStumpErrRate
0.02
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
MaxKurtosisOfNumericAtts
1.7
Maximum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
6.77
Minimum of means among attributes of the numeric type.
Quartile2MutualInformation
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Show all 107 properties

15 tasks

Supervised Classification on mfeat-factors
568 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: binaryClass
Supervised Classification on mfeat-factors
198 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: binaryClass
Supervised Classification on mfeat-factors
0 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: binaryClass
Supervised Data Stream Classification on mfeat-factors
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: binaryClass
Clustering on mfeat-factors
0 runs - estimation_procedure: 50 times Clustering
Clustering on mfeat-factors
0 runs - estimation_procedure: 50 times Clustering
Clustering on mfeat-factors
0 runs - estimation_procedure: 50 times Clustering
Clustering on mfeat-factors
0 runs - estimation_procedure: 50 times Clustering
Clustering on mfeat-factors
0 runs - estimation_procedure: 50 times Clustering
Clustering on mfeat-factors
0 runs - estimation_procedure: 50 times Clustering
Clustering on mfeat-factors
0 runs
Clustering on mfeat-factors
0 runs - estimation_procedure: 50 times Clustering
Clustering on mfeat-factors
0 runs - estimation_procedure: 50 times Clustering
Clustering on mfeat-factors
0 runs - estimation_procedure: 50 times Clustering
Clustering on mfeat-factors
0 runs - estimation_procedure: 50 times Clustering
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