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mfeat-factors

mfeat-factors

active ARFF Publicly available Visibility: public Uploaded 04-10-2014 by Joaquin Vanschoren
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  • Data Science Healthcare Image Processing Medical Science mythbusting_1 study_1 study_15 study_20 study_41 study_7
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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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att208numeric472 unique values
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att210numeric391 unique values
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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.
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_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
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
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
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
ClassEntropy
0.47
Entropy of the target attribute values.
kNN1NKappa
0.96
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
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.
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
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.
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
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.
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
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.
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.
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.
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.
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.
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
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
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
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
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
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
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
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
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
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
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
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
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
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_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
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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