Data
mfeat-karhunen

mfeat-karhunen

active ARFF Publicly available Visibility: public Uploaded 06-04-2014 by Jan van Rijn
0 likes downloaded by 19 people , 21 total downloads 0 issues 0 downvotes
  • OpenML-CC18 OpenML100 study_1 study_123 study_14 study_34 study_37 study_41 study_52 study_7 study_70 study_76 study_98 study_99 uci
Issue #Downvotes for this reason By


Loading wiki
Help us complete this description Edit
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
att1numeric1994 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
att17numeric1994 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
att33numeric1994 unique values
0 missing
att34numeric1994 unique values
0 missing
att35numeric1994 unique values
0 missing
att36numeric1994 unique values
0 missing
att37numeric1994 unique values
0 missing
att38numeric1994 unique values
0 missing
att39numeric1994 unique values
0 missing
att40numeric1994 unique values
0 missing
att41numeric1993 unique values
0 missing
att42numeric1994 unique values
0 missing
att43numeric1994 unique values
0 missing
att44numeric1994 unique values
0 missing
att45numeric1994 unique values
0 missing
att46numeric1994 unique values
0 missing
att47numeric1994 unique values
0 missing
att48numeric1994 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

107 properties

2000
Number of instances (rows) of the dataset.
65
Number of attributes (columns) of the dataset.
10
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
64
Number of numeric attributes.
1
Number of nominal attributes.
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
0
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
0.21
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
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
0.66
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.89
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
10
Average number of distinct values among the attributes of the nominal type.
-0.1
First quartile of skewness among attributes of the numeric type.
0.77
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
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
0
Standard deviation of the number of distinct values among attributes of the nominal type.
0.21
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
-0
Mean skewness among attributes of the numeric type.
1.14
First quartile of standard deviation of attributes of the numeric type.
0.92
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
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
0.97
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.77
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
2.15
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
0.21
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
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
0.05
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
10
Percentage of instances belonging to the most frequent class.
Minimal entropy among attributes.
-0.02
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.77
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
3.32
Entropy of the target attribute values.
0.94
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
200
Number of instances belonging to the most frequent class.
-0.94
Minimum kurtosis among attributes of the numeric type.
0
Second quartile (Median) of means among attributes of the numeric type.
0.92
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.69
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum entropy among attributes.
-1.82
Minimum of means among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.21
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.8
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
0.58
Maximum kurtosis among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
-0.02
Second quartile (Median) of skewness among attributes of the numeric type.
0.77
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.11
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
2.89
Maximum of means among attributes of the numeric type.
10
The minimal number of distinct values among attributes of the nominal type.
0
Percentage of binary attributes.
1.65
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.83
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.03
Number of attributes divided by the number of instances.
Maximum mutual information between the nominal attributes and the target attribute.
-0.34
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
0.31
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
10
The maximum number of distinct values among attributes of the nominal type.
0.89
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
0.07
Third quartile of kurtosis among attributes of the numeric type.
1
Average class difference between consecutive instances.
0.66
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.89
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
0.42
Maximum skewness among attributes of the numeric type.
10
Percentage of instances belonging to the least frequent class.
98.46
Percentage of numeric attributes.
0.33
Third quartile of means among attributes of the numeric type.
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
0.83
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.21
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
7.69
Maximum standard deviation of attributes of the numeric type.
200
Number of instances belonging to the least frequent class.
1.54
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
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
0.31
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.77
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Average entropy of the attributes.
1
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of entropy among attributes.
0.06
Third quartile of skewness among attributes of the numeric type.
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
0.66
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.89
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
-0.05
Mean kurtosis among attributes of the numeric type.
0.07
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
-0.15
First quartile of kurtosis among attributes of the numeric type.
2.66
Third quartile of standard deviation of attributes of the numeric type.
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
0.83
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.21
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0.05
Mean of means among attributes of the numeric type.
Average mutual information between the nominal attributes and the target attribute.
0.92
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
-0.3
First quartile of means among attributes of the numeric type.
0.92
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
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
0.31
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.77
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001

57 tasks

15852 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: class
315 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: class
306 runs - estimation_procedure: 5 times 2-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
169 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
31 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: precision - target_feature: class
0 runs - estimation_procedure: Leave one out - evaluation_measure: predictive_accuracy - target_feature: class
0 runs - estimation_procedure: 33% Holdout set - target_feature: class
317 runs - estimation_procedure: 10-fold Learning Curve - evaluation_measure: predictive_accuracy - target_feature: class
175 runs - estimation_procedure: 10 times 10-fold Learning Curve - evaluation_measure: predictive_accuracy - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
25 runs - estimation_procedure: Interleaved Test then Train - target_feature: class
0 runs - target_feature: class
1307 runs - target_feature: class
1306 runs - target_feature: class
1306 runs - target_feature: class
1305 runs - target_feature: class
1304 runs - target_feature: class
1304 runs - target_feature: class
1304 runs - target_feature: class
1302 runs - target_feature: class
1301 runs - target_feature: class
1298 runs - target_feature: class
0 runs - target_feature: class
0 runs - target_feature: class
0 runs - target_feature: class
0 runs - target_feature: class
0 runs - target_feature: class
0 runs - target_feature: class
0 runs - target_feature: class
0 runs - target_feature: class
0 runs - target_feature: class
0 runs - target_feature: class
0 runs - target_feature: class
0 runs - target_feature: class
0 runs - target_feature: class
0 runs - target_feature: class
0 runs - target_feature: class
0 runs - target_feature: class
0 runs - target_feature: class
0 runs - target_feature: class
0 runs - target_feature: class
0 runs - target_feature: class
0 runs - target_feature: class
0 runs - target_feature: class
0 runs - target_feature: class
0 runs - target_feature: class
0 runs - target_feature: class
0 runs - target_feature: class
0 runs - target_feature: class
0 runs - target_feature: class
0 runs - target_feature: class
0 runs - target_feature: class
Define a new task