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mfeat-karhunen

mfeat-karhunen

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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: Karhunen 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 64 descriptors from the Karhunen-Loeve Transform, a linear transform that corresponds to the projection of the images on the eigenvectors of a covariant matrix. Also see: M.D. Garris et al: NIST Form-Based Handprint Recognition System. Internal Report. National Institute of Standards and Technology, NISTIR 5469, 1994. ### 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

65 features

class (target)nominal10 unique values
0 missing
att48numeric1994 unique values
0 missing
att34numeric1994 unique values
0 missing
att47numeric1994 unique values
0 missing
att46numeric1994 unique values
0 missing
att45numeric1994 unique values
0 missing
att44numeric1994 unique values
0 missing
att43numeric1994 unique values
0 missing
att42numeric1994 unique values
0 missing
att41numeric1993 unique values
0 missing
att40numeric1994 unique values
0 missing
att39numeric1994 unique values
0 missing
att38numeric1994 unique values
0 missing
att37numeric1994 unique values
0 missing
att36numeric1994 unique values
0 missing
att35numeric1994 unique values
0 missing
att33numeric1994 unique values
0 missing
att49numeric1994 unique values
0 missing
att50numeric1994 unique values
0 missing
att51numeric1994 unique values
0 missing
att52numeric1994 unique values
0 missing
att53numeric1994 unique values
0 missing
att54numeric1994 unique values
0 missing
att55numeric1994 unique values
0 missing
att56numeric1994 unique values
0 missing
att57numeric1994 unique values
0 missing
att58numeric1994 unique values
0 missing
att59numeric1994 unique values
0 missing
att60numeric1994 unique values
0 missing
att61numeric1994 unique values
0 missing
att62numeric1994 unique values
0 missing
att63numeric1993 unique values
0 missing
att64numeric1994 unique values
0 missing
att17numeric1994 unique values
0 missing
att2numeric1994 unique values
0 missing
att3numeric1994 unique values
0 missing
att4numeric1994 unique values
0 missing
att5numeric1994 unique values
0 missing
att6numeric1994 unique values
0 missing
att7numeric1994 unique values
0 missing
att8numeric1994 unique values
0 missing
att9numeric1994 unique values
0 missing
att10numeric1994 unique values
0 missing
att11numeric1994 unique values
0 missing
att12numeric1994 unique values
0 missing
att13numeric1994 unique values
0 missing
att14numeric1994 unique values
0 missing
att15numeric1994 unique values
0 missing
att16numeric1994 unique values
0 missing
att1numeric1994 unique values
0 missing
att18numeric1994 unique values
0 missing
att19numeric1994 unique values
0 missing
att20numeric1993 unique values
0 missing
att21numeric1994 unique values
0 missing
att22numeric1994 unique values
0 missing
att23numeric1994 unique values
0 missing
att24numeric1994 unique values
0 missing
att25numeric1994 unique values
0 missing
att26numeric1994 unique values
0 missing
att27numeric1994 unique values
0 missing
att28numeric1994 unique values
0 missing
att29numeric1994 unique values
0 missing
att30numeric1994 unique values
0 missing
att31numeric1994 unique values
0 missing
att32numeric1994 unique values
0 missing
Show all 65 features

107 properties

NumberOfInstances
2000
Number of instances (rows) of the dataset.
NumberOfFeatures
65
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
64
Number of numeric attributes.
NumberOfSymbolicFeatures
1
Number of nominal attributes.
AutoCorrelation
1
Average class difference between consecutive instances.
CfsSubsetEval_DecisionStumpAUC
0.89
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
CfsSubsetEval_DecisionStumpErrRate
0.21
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
CfsSubsetEval_DecisionStumpKappa
0.77
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
CfsSubsetEval_NaiveBayesAUC
0.89
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
CfsSubsetEval_NaiveBayesErrRate
0.21
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
CfsSubsetEval_NaiveBayesKappa
0.77
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
0.89
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
CfsSubsetEval_kNN1NErrRate
0.21
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
CfsSubsetEval_kNN1NKappa
0.77
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
ClassEntropy
3.32
Entropy of the target attribute values.
DecisionStumpAUC
0.69
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpErrRate
0.8
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpKappa
0.11
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
Dimensionality
0.03
Number of attributes divided by the number of instances.
EquivalentNumberOfAtts
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
J48.00001.AUC
0.89
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.ErrRate
0.21
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.Kappa
0.77
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.0001.AUC
0.89
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.ErrRate
0.21
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.Kappa
0.77
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.001.AUC
0.89
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.ErrRate
0.21
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.Kappa
0.77
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
MajorityClassPercentage
10
Percentage of instances belonging to the most frequent class.
MajorityClassSize
200
Number of instances belonging to the most frequent class.
MaxAttributeEntropy
Maximum entropy among attributes.
MaxKurtosisOfNumericAtts
0.58
Maximum kurtosis among attributes of the numeric type.
MaxMeansOfNumericAtts
2.89
Maximum of means among attributes of the numeric type.
MaxMutualInformation
Maximum mutual information between the nominal attributes and the target attribute.
MaxNominalAttDistinctValues
10
The maximum number of distinct values among attributes of the nominal type.
MaxSkewnessOfNumericAtts
0.42
Maximum skewness among attributes of the numeric type.
MaxStdDevOfNumericAtts
7.69
Maximum standard deviation of attributes of the numeric type.
MeanAttributeEntropy
Average entropy of the attributes.
MeanKurtosisOfNumericAtts
-0.05
Mean kurtosis among attributes of the numeric type.
MeanMeansOfNumericAtts
0.05
Mean of means among attributes of the numeric type.
MeanMutualInformation
Average mutual information between the nominal attributes and the target attribute.
MeanNoiseToSignalRatio
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
MeanNominalAttDistinctValues
10
Average number of distinct values among the attributes of the nominal type.
MeanSkewnessOfNumericAtts
-0
Mean skewness among attributes of the numeric type.
MeanStdDevOfNumericAtts
2.15
Mean standard deviation of attributes of the numeric type.
MinAttributeEntropy
Minimal entropy among attributes.
MinKurtosisOfNumericAtts
-0.94
Minimum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
-1.82
Minimum of means among attributes of the numeric type.
MinMutualInformation
Minimal mutual information between the nominal attributes and the target attribute.
MinNominalAttDistinctValues
10
The minimal number of distinct values among attributes of the nominal type.
MinSkewnessOfNumericAtts
-0.34
Minimum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
0.89
Minimum standard deviation of attributes of the numeric type.
MinorityClassPercentage
10
Percentage of instances belonging to the least frequent class.
MinorityClassSize
200
Number of instances belonging to the least frequent class.
NaiveBayesAUC
1
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesErrRate
0.07
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesKappa
0.92
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NumberOfBinaryFeatures
0
Number of binary attributes.
PercentageOfBinaryFeatures
0
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
PercentageOfMissingValues
0
Percentage of missing values.
PercentageOfNumericFeatures
98.46
Percentage of numeric attributes.
PercentageOfSymbolicFeatures
1.54
Percentage of nominal attributes.
Quartile1AttributeEntropy
First quartile of entropy among attributes.
Quartile1KurtosisOfNumericAtts
-0.15
First quartile of kurtosis among attributes of the numeric type.
Quartile1MeansOfNumericAtts
-0.3
First quartile of means among attributes of the numeric type.
Quartile1MutualInformation
First quartile of mutual information between the nominal attributes and the target attribute.
Quartile1SkewnessOfNumericAtts
-0.1
First quartile of skewness among attributes of the numeric type.
Quartile1StdDevOfNumericAtts
1.14
First quartile of standard deviation of attributes of the numeric type.
Quartile2AttributeEntropy
Second quartile (Median) of entropy among attributes.
Quartile2KurtosisOfNumericAtts
-0.02
Second quartile (Median) of kurtosis among attributes of the numeric type.
Quartile2MeansOfNumericAtts
0
Second quartile (Median) of means among attributes of the numeric type.
Quartile2MutualInformation
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Quartile2SkewnessOfNumericAtts
-0.02
Second quartile (Median) of skewness among attributes of the numeric type.
Quartile2StdDevOfNumericAtts
1.65
Second quartile (Median) of standard deviation of attributes of the numeric type.
Quartile3AttributeEntropy
Third quartile of entropy among attributes.
Quartile3KurtosisOfNumericAtts
0.07
Third quartile of kurtosis among attributes of the numeric type.
Quartile3MeansOfNumericAtts
0.33
Third quartile of means among attributes of the numeric type.
Quartile3MutualInformation
Third quartile of mutual information between the nominal attributes and the target attribute.
Quartile3SkewnessOfNumericAtts
0.06
Third quartile of skewness among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
2.66
Third quartile of standard deviation of attributes of the numeric type.
REPTreeDepth1AUC
0.92
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1ErrRate
0.21
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1Kappa
0.77
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth2AUC
0.92
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2ErrRate
0.21
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2Kappa
0.77
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth3AUC
0.92
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3ErrRate
0.21
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3Kappa
0.77
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
RandomTreeDepth1AUC
0.83
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1ErrRate
0.31
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1Kappa
0.66
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth2AUC
0.83
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2ErrRate
0.31
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2Kappa
0.66
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth3AUC
0.83
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3ErrRate
0.31
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3Kappa
0.66
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
StdvNominalAttDistinctValues
0
Standard deviation of the number of distinct values among attributes of the nominal type.
kNN1NAUC
0.97
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NErrRate
0.05
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NKappa
0.94
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
Show all 107 properties

72 tasks

Supervised Classification on mfeat-karhunen
24478 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: class
Supervised Classification on mfeat-karhunen
315 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: class
Supervised Classification on mfeat-karhunen
307 runs - estimation_procedure: 5 times 2-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
Supervised Classification on mfeat-karhunen
169 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
Supervised Classification on mfeat-karhunen
31 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: precision - target_feature: class
Supervised Classification on mfeat-karhunen
31 runs - estimation_procedure: 5 times 2-fold Crossvalidation - target_feature: class
Supervised Classification on mfeat-karhunen
0 runs - estimation_procedure: Leave one out - evaluation_measure: predictive_accuracy - target_feature: class
Supervised Classification on mfeat-karhunen
0 runs - estimation_procedure: 33% Holdout set - target_feature: class
Supervised Classification on mfeat-karhunen
0 runs - estimation_procedure: 4-fold Crossvalidation - target_feature: class
Learning Curve on mfeat-karhunen
317 runs - estimation_procedure: 10-fold Learning Curve - evaluation_measure: predictive_accuracy - target_feature: class
Learning Curve on mfeat-karhunen
175 runs - estimation_procedure: 10 times 10-fold Learning Curve - evaluation_measure: predictive_accuracy - target_feature: class
Learning Curve on mfeat-karhunen
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on mfeat-karhunen
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on mfeat-karhunen
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on mfeat-karhunen
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on mfeat-karhunen
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on mfeat-karhunen
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on mfeat-karhunen
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on mfeat-karhunen
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Supervised Data Stream Classification on mfeat-karhunen
25 runs - estimation_procedure: Interleaved Test then Train - target_feature: class
Clustering on mfeat-karhunen
0 runs - target_feature: class
Clustering on mfeat-karhunen
0 runs
Clustering on mfeat-karhunen
0 runs - estimation_procedure: 50 times Clustering
Clustering on mfeat-karhunen
0 runs - estimation_procedure: 50 times Clustering
Clustering on mfeat-karhunen
0 runs - estimation_procedure: 50 times Clustering
Clustering on mfeat-karhunen
0 runs - estimation_procedure: 50 times Clustering
Clustering on mfeat-karhunen
0 runs - estimation_procedure: 50 times Clustering
Clustering on mfeat-karhunen
0 runs - estimation_procedure: 50 times Clustering
Clustering on mfeat-karhunen
0 runs - estimation_procedure: 50 times Clustering
Clustering on mfeat-karhunen
0 runs - estimation_procedure: 50 times Clustering
Clustering on mfeat-karhunen
0 runs - estimation_procedure: 50 times Clustering
Clustering on mfeat-karhunen
0 runs - estimation_procedure: 50 times Clustering
Subgroup Discovery on mfeat-karhunen
1307 runs - target_feature: class
Subgroup Discovery on mfeat-karhunen
1306 runs - target_feature: class
Subgroup Discovery on mfeat-karhunen
1306 runs - target_feature: class
Subgroup Discovery on mfeat-karhunen
1305 runs - target_feature: class
Subgroup Discovery on mfeat-karhunen
1304 runs - target_feature: class
Subgroup Discovery on mfeat-karhunen
1304 runs - target_feature: class
Subgroup Discovery on mfeat-karhunen
1304 runs - target_feature: class
Subgroup Discovery on mfeat-karhunen
1302 runs - target_feature: class
Subgroup Discovery on mfeat-karhunen
1301 runs - target_feature: class
Subgroup Discovery on mfeat-karhunen
1298 runs - target_feature: class
Subgroup Discovery on mfeat-karhunen
0 runs - target_feature: class
Subgroup Discovery on mfeat-karhunen
0 runs - target_feature: class
Subgroup Discovery on mfeat-karhunen
0 runs - target_feature: class
Subgroup Discovery on mfeat-karhunen
0 runs - target_feature: class
Subgroup Discovery on mfeat-karhunen
0 runs - target_feature: class
Subgroup Discovery on mfeat-karhunen
0 runs - target_feature: class
Subgroup Discovery on mfeat-karhunen
0 runs - target_feature: class
Subgroup Discovery on mfeat-karhunen
0 runs - target_feature: class
Subgroup Discovery on mfeat-karhunen
0 runs - target_feature: class
Subgroup Discovery on mfeat-karhunen
0 runs - target_feature: class
Subgroup Discovery on mfeat-karhunen
0 runs - target_feature: class
Subgroup Discovery on mfeat-karhunen
0 runs - target_feature: class
Subgroup Discovery on mfeat-karhunen
0 runs - target_feature: class
Subgroup Discovery on mfeat-karhunen
0 runs - target_feature: class
Subgroup Discovery on mfeat-karhunen
0 runs - target_feature: class
Subgroup Discovery on mfeat-karhunen
0 runs - target_feature: class
Subgroup Discovery on mfeat-karhunen
0 runs - target_feature: class
Subgroup Discovery on mfeat-karhunen
0 runs - target_feature: class
Subgroup Discovery on mfeat-karhunen
0 runs - target_feature: class
Subgroup Discovery on mfeat-karhunen
0 runs - target_feature: class
Subgroup Discovery on mfeat-karhunen
0 runs - target_feature: class
Subgroup Discovery on mfeat-karhunen
0 runs - target_feature: class
Subgroup Discovery on mfeat-karhunen
0 runs - target_feature: class
Subgroup Discovery on mfeat-karhunen
0 runs - target_feature: class
Subgroup Discovery on mfeat-karhunen
0 runs - target_feature: class
Subgroup Discovery on mfeat-karhunen
0 runs - target_feature: class
Subgroup Discovery on mfeat-karhunen
0 runs - target_feature: class
Subgroup Discovery on mfeat-karhunen
0 runs - target_feature: class
Subgroup Discovery on mfeat-karhunen
0 runs - target_feature: class
Subgroup Discovery on mfeat-karhunen
0 runs - target_feature: class
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