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mfeat-factors

mfeat-factors

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  • OpenML-CC18 OpenML100 Pattern Recognition Statistics study_1 study_123 study_14 study_218 study_34 study_37 study_41 study_50 study_7 study_70 study_76 study_98 study_99 uci
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Author: Robert P.W. Duin, Department of Applied Physics, Delft University of Technology Source: [UCI](https://archive.ics.uci.edu/ml/datasets/Multiple+Features) - 1998 Please cite: [UCI](https://archive.ics.uci.edu/ml/citation_policy.html) Multiple Features Dataset: Factors One of a set of 6 datasets describing features of handwritten numerals (0 - 9) extracted from a collection of Dutch utility maps. Corresponding patterns in different datasets correspond to the same original character. 200 instances per class (for a total of 2,000 instances) have been digitized in binary images. ### Attribute Information The attributes represent 216 profile correlations. No more information is known. ### Relevant Papers A slightly different version of the database is used in M. van Breukelen, R.P.W. Duin, D.M.J. Tax, and J.E. den Hartog, Handwritten digit recognition by combined classifiers, Kybernetika, vol. 34, no. 4, 1998, 381-386. The database as is is used in: A.K. Jain, R.P.W. Duin, J. Mao, Statistical Pattern Recognition: A Review, IEEE Transactions on Pattern Analysis and Machine Intelligence archive, Volume 22 Issue 1, January 2000

217 features

class (target)nominal10 unique values
0 missing
att1numeric390 unique values
0 missing
att2numeric446 unique values
0 missing
att3numeric541 unique values
0 missing
att4numeric440 unique values
0 missing
att5numeric252 unique values
0 missing
att6numeric419 unique values
0 missing
att7numeric43 unique values
0 missing
att8numeric39 unique values
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att9numeric40 unique values
0 missing
att10numeric18 unique values
0 missing
att11numeric19 unique values
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att12numeric18 unique values
0 missing
att13numeric336 unique values
0 missing
att14numeric420 unique values
0 missing
att15numeric421 unique values
0 missing
att16numeric351 unique values
0 missing
att17numeric257 unique values
0 missing
att18numeric405 unique values
0 missing
att19numeric42 unique values
0 missing
att20numeric41 unique values
0 missing
att21numeric41 unique values
0 missing
att22numeric25 unique values
0 missing
att23numeric18 unique values
0 missing
att24numeric21 unique values
0 missing
att25numeric302 unique values
0 missing
att26numeric439 unique values
0 missing
att27numeric323 unique values
0 missing
att28numeric323 unique values
0 missing
att29numeric422 unique values
0 missing
att30numeric377 unique values
0 missing
att31numeric41 unique values
0 missing
att32numeric42 unique values
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att33numeric44 unique values
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att34numeric20 unique values
0 missing
att35numeric22 unique values
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att36numeric23 unique values
0 missing
att37numeric402 unique values
0 missing
att38numeric483 unique values
0 missing
att39numeric468 unique values
0 missing
att40numeric411 unique values
0 missing
att41numeric326 unique values
0 missing
att42numeric364 unique values
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att43numeric34 unique values
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att44numeric39 unique values
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att45numeric44 unique values
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att46numeric23 unique values
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att47numeric22 unique values
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att48numeric23 unique values
0 missing
att49numeric300 unique values
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att50numeric484 unique values
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att51numeric471 unique values
0 missing
att52numeric413 unique values
0 missing
att53numeric375 unique values
0 missing
att54numeric367 unique values
0 missing
att55numeric42 unique values
0 missing
att56numeric40 unique values
0 missing
att57numeric44 unique values
0 missing
att58numeric24 unique values
0 missing
att59numeric23 unique values
0 missing
att60numeric20 unique values
0 missing
att61numeric302 unique values
0 missing
att62numeric348 unique values
0 missing
att63numeric464 unique values
0 missing
att64numeric404 unique values
0 missing
att65numeric449 unique values
0 missing
att66numeric383 unique values
0 missing
att67numeric41 unique values
0 missing
att68numeric38 unique values
0 missing
att69numeric43 unique values
0 missing
att70numeric20 unique values
0 missing
att71numeric20 unique values
0 missing
att72numeric25 unique values
0 missing
att73numeric304 unique values
0 missing
att74numeric361 unique values
0 missing
att75numeric435 unique values
0 missing
att76numeric395 unique values
0 missing
att77numeric313 unique values
0 missing
att78numeric432 unique values
0 missing
att79numeric43 unique values
0 missing
att80numeric40 unique values
0 missing
att81numeric41 unique values
0 missing
att82numeric25 unique values
0 missing
att83numeric20 unique values
0 missing
att84numeric20 unique values
0 missing
att85numeric301 unique values
0 missing
att86numeric460 unique values
0 missing
att87numeric427 unique values
0 missing
att88numeric448 unique values
0 missing
att89numeric350 unique values
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att90numeric405 unique values
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att91numeric42 unique values
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att92numeric36 unique values
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att93numeric45 unique values
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att94numeric25 unique values
0 missing
att95numeric18 unique values
0 missing
att96numeric23 unique values
0 missing
att97numeric473 unique values
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att98numeric390 unique values
0 missing
att99numeric352 unique values
0 missing
att100numeric494 unique values
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att101numeric268 unique values
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att102numeric394 unique values
0 missing
att103numeric39 unique values
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att104numeric44 unique values
0 missing
att105numeric46 unique values
0 missing
att106numeric23 unique values
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att107numeric22 unique values
0 missing
att108numeric20 unique values
0 missing
att109numeric450 unique values
0 missing
att110numeric342 unique values
0 missing
att111numeric590 unique values
0 missing
att112numeric297 unique values
0 missing
att113numeric407 unique values
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att114numeric401 unique values
0 missing
att115numeric44 unique values
0 missing
att116numeric30 unique values
0 missing
att117numeric41 unique values
0 missing
att118numeric18 unique values
0 missing
att119numeric23 unique values
0 missing
att120numeric24 unique values
0 missing
att121numeric279 unique values
0 missing
att122numeric341 unique values
0 missing
att123numeric548 unique values
0 missing
att124numeric398 unique values
0 missing
att125numeric411 unique values
0 missing
att126numeric374 unique values
0 missing
att127numeric43 unique values
0 missing
att128numeric32 unique values
0 missing
att129numeric45 unique values
0 missing
att130numeric23 unique values
0 missing
att131numeric19 unique values
0 missing
att132numeric26 unique values
0 missing
att133numeric364 unique values
0 missing
att134numeric349 unique values
0 missing
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
0 missing
att141numeric35 unique values
0 missing
att142numeric23 unique values
0 missing
att143numeric19 unique values
0 missing
att144numeric23 unique values
0 missing
att145numeric278 unique values
0 missing
att146numeric434 unique values
0 missing
att147numeric501 unique values
0 missing
att148numeric492 unique values
0 missing
att149numeric302 unique values
0 missing
att150numeric355 unique values
0 missing
att151numeric37 unique values
0 missing
att152numeric32 unique values
0 missing
att153numeric35 unique values
0 missing
att154numeric22 unique values
0 missing
att155numeric18 unique values
0 missing
att156numeric25 unique values
0 missing
att157numeric379 unique values
0 missing
att158numeric398 unique values
0 missing
att159numeric357 unique values
0 missing
att160numeric403 unique values
0 missing
att161numeric327 unique values
0 missing
att162numeric449 unique values
0 missing
att163numeric44 unique values
0 missing
att164numeric34 unique values
0 missing
att165numeric46 unique values
0 missing
att166numeric25 unique values
0 missing
att167numeric22 unique values
0 missing
att168numeric19 unique values
0 missing
att169numeric359 unique values
0 missing
att170numeric394 unique values
0 missing
att171numeric435 unique values
0 missing
att172numeric314 unique values
0 missing
att173numeric454 unique values
0 missing
att174numeric381 unique values
0 missing
att175numeric44 unique values
0 missing
att176numeric39 unique values
0 missing
att177numeric45 unique values
0 missing
att178numeric18 unique values
0 missing
att179numeric22 unique values
0 missing
att180numeric26 unique values
0 missing
att181numeric499 unique values
0 missing
att182numeric402 unique values
0 missing
att183numeric540 unique values
0 missing
att184numeric416 unique values
0 missing
att185numeric460 unique values
0 missing
att186numeric434 unique values
0 missing
att187numeric43 unique values
0 missing
att188numeric43 unique values
0 missing
att189numeric45 unique values
0 missing
att190numeric18 unique values
0 missing
att191numeric25 unique values
0 missing
att192numeric25 unique values
0 missing
att193numeric445 unique values
0 missing
att194numeric517 unique values
0 missing
att195numeric474 unique values
0 missing
att196numeric458 unique values
0 missing
att197numeric255 unique values
0 missing
att198numeric463 unique values
0 missing
att199numeric46 unique values
0 missing
att200numeric41 unique values
0 missing
att201numeric44 unique values
0 missing
att202numeric25 unique values
0 missing
att203numeric25 unique values
0 missing
att204numeric19 unique values
0 missing
att205numeric303 unique values
0 missing
att206numeric330 unique values
0 missing
att207numeric550 unique values
0 missing
att208numeric472 unique values
0 missing
att209numeric292 unique values
0 missing
att210numeric391 unique values
0 missing
att211numeric30 unique values
0 missing
att212numeric38 unique values
0 missing
att213numeric36 unique values
0 missing
att214numeric15 unique values
0 missing
att215numeric15 unique values
0 missing
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
10
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.
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
0.94
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
0.89
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
J48.00001.ErrRate
0.14
Error rate 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
0.13
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
0.19
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
J48.00001.Kappa
0.85
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
MeanKurtosisOfNumericAtts
-0.32
Mean kurtosis among attributes of the numeric type.
NaiveBayesAUC
0.99
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
0.85
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
0.79
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
J48.0001.AUC
0.93
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
MeanMeansOfNumericAtts
318.27
Mean of means among attributes of the numeric type.
NaiveBayesErrRate
0.08
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
0.94
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
0.89
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
J48.0001.ErrRate
0.14
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
MeanMutualInformation
Average mutual information between the nominal attributes and the target attribute.
NaiveBayesKappa
0.92
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
0.13
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
0.19
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
J48.0001.Kappa
0.85
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
MeanNoiseToSignalRatio
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
NumberOfBinaryFeatures
0
Number of binary attributes.
Quartile1MutualInformation
First quartile of mutual information between the nominal attributes and the target attribute.
REPTreeDepth1ErrRate
0.16
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
CfsSubsetEval_NaiveBayesKappa
0.85
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
0.79
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
J48.001.AUC
0.93
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
MeanNominalAttDistinctValues
10
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
0.83
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
CfsSubsetEval_kNN1NAUC
0.94
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
0.14
Error rate 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_kNN1NErrRate
0.13
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
0.98
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
J48.001.Kappa
0.85
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
MeanStdDevOfNumericAtts
49.58
Mean standard deviation of attributes of the numeric type.
Quartile2AttributeEntropy
Second quartile (Median) of entropy among attributes.
REPTreeDepth2ErrRate
0.16
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
CfsSubsetEval_kNN1NKappa
0.85
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
0.04
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
MajorityClassPercentage
10
Percentage 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
0.83
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
ClassEntropy
3.32
Entropy of the target attribute values.
kNN1NKappa
0.95
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
MajorityClassSize
200
Number of instances belonging to the most frequent class.
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.
REPTreeDepth3AUC
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
DecisionStumpAUC
0.72
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
MaxAttributeEntropy
Maximum entropy among attributes.
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.
REPTreeDepth3ErrRate
0.16
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
DecisionStumpErrRate
0.81
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
MaxKurtosisOfNumericAtts
1.7
Maximum kurtosis 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.
REPTreeDepth3Kappa
0.83
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
DecisionStumpKappa
0.1
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
MaxMeansOfNumericAtts
1141.57
Maximum of means among attributes of the numeric type.
MinNominalAttDistinctValues
10
The minimal number of distinct values among attributes of the nominal type.
PercentageOfBinaryFeatures
0
Percentage of binary attributes.
Quartile2StdDevOfNumericAtts
30.29
Second quartile (Median) of standard deviation of attributes of the numeric type.
RandomTreeDepth1AUC
0.89
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.
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.
RandomTreeDepth1ErrRate
0.19
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
10
The maximum number of distinct values among attributes of the nominal 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.
RandomTreeDepth1Kappa
0.79
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
J48.00001.AUC
0.93
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.
Show all 107 properties

75 tasks

Supervised Classification on mfeat-factors
23377 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: class
Supervised Classification on mfeat-factors
308 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: class
Supervised Classification on mfeat-factors
302 runs - estimation_procedure: 5 times 2-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
Supervised Classification on mfeat-factors
172 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
Supervised Classification on mfeat-factors
43 runs - estimation_procedure: 5 times 2-fold Crossvalidation - target_feature: class
Supervised Classification on mfeat-factors
31 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: precision - target_feature: class
Supervised Classification on mfeat-factors
4 runs - estimation_procedure: 33% Holdout set - target_feature: class
Supervised Classification on mfeat-factors
0 runs - estimation_procedure: Leave one out - evaluation_measure: predictive_accuracy - target_feature: class
Supervised Classification on mfeat-factors
0 runs - estimation_procedure: 20% Holdout (Ordered) - evaluation_measure: predictive_accuracy - target_feature: class
Supervised Classification on mfeat-factors
0 runs - estimation_procedure: 4-fold Crossvalidation - target_feature: class
Supervised Classification on mfeat-factors
0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
Learning Curve on mfeat-factors
337 runs - estimation_procedure: 10-fold Learning Curve - evaluation_measure: predictive_accuracy - target_feature: class
Learning Curve on mfeat-factors
179 runs - estimation_procedure: 10 times 10-fold Learning Curve - evaluation_measure: predictive_accuracy - target_feature: class
Learning Curve on mfeat-factors
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on mfeat-factors
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on mfeat-factors
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on mfeat-factors
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on mfeat-factors
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on mfeat-factors
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on mfeat-factors
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on mfeat-factors
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Supervised Data Stream Classification on mfeat-factors
25 runs - estimation_procedure: Interleaved Test then Train - target_feature: class
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 - target_feature: class
Clustering on mfeat-factors
0 runs - estimation_procedure: 50 times Clustering
Clustering on mfeat-factors
0 runs - estimation_procedure: 50 times Clustering - target_feature: class
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
Subgroup Discovery on mfeat-factors
1309 runs - target_feature: class
Subgroup Discovery on mfeat-factors
1304 runs - target_feature: class
Subgroup Discovery on mfeat-factors
1302 runs - target_feature: class
Subgroup Discovery on mfeat-factors
1301 runs - target_feature: class
Subgroup Discovery on mfeat-factors
1301 runs - target_feature: class
Subgroup Discovery on mfeat-factors
1301 runs - target_feature: class
Subgroup Discovery on mfeat-factors
1300 runs - target_feature: class
Subgroup Discovery on mfeat-factors
1300 runs - target_feature: class
Subgroup Discovery on mfeat-factors
1300 runs - target_feature: class
Subgroup Discovery on mfeat-factors
1298 runs - target_feature: class
Subgroup Discovery on mfeat-factors
0 runs - target_feature: class
Subgroup Discovery on mfeat-factors
0 runs - target_feature: class
Subgroup Discovery on mfeat-factors
0 runs - target_feature: class
Subgroup Discovery on mfeat-factors
0 runs - target_feature: class
Subgroup Discovery on mfeat-factors
0 runs - target_feature: class
Subgroup Discovery on mfeat-factors
0 runs - target_feature: class
Subgroup Discovery on mfeat-factors
0 runs - target_feature: class
Subgroup Discovery on mfeat-factors
0 runs - target_feature: class
Subgroup Discovery on mfeat-factors
0 runs - target_feature: class
Subgroup Discovery on mfeat-factors
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Subgroup Discovery on mfeat-factors
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Subgroup Discovery on mfeat-factors
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Subgroup Discovery on mfeat-factors
0 runs - target_feature: class
Subgroup Discovery on mfeat-factors
0 runs - target_feature: class
Subgroup Discovery on mfeat-factors
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Subgroup Discovery on mfeat-factors
0 runs - target_feature: class
Subgroup Discovery on mfeat-factors
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Subgroup Discovery on mfeat-factors
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Subgroup Discovery on mfeat-factors
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Subgroup Discovery on mfeat-factors
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Subgroup Discovery on mfeat-factors
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Subgroup Discovery on mfeat-factors
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Subgroup Discovery on mfeat-factors
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Subgroup Discovery on mfeat-factors
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Subgroup Discovery on mfeat-factors
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Subgroup Discovery on mfeat-factors
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Subgroup Discovery on mfeat-factors
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Subgroup Discovery on mfeat-factors
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Subgroup Discovery on mfeat-factors
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Subgroup Discovery on mfeat-factors
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