Data
aloi

aloi

active Sparse_ARFF Publicly available Visibility: public Uploaded 15-06-2015 by Farooq Zuberi
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Author: Anderson Rocha Source: http://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/multiclass.html Please cite: #Dataset from the LIBSVM multiclass data repository.

129 features

class (target)numeric1000 unique values
0 missing
att_1numeric10 unique values
0 missing
att_2numeric10 unique values
0 missing
att_3numeric10 unique values
0 missing
att_4numeric10 unique values
0 missing
att_5numeric10 unique values
0 missing
att_6numeric10 unique values
0 missing
att_7numeric10 unique values
0 missing
att_8numeric10 unique values
0 missing
att_9numeric10 unique values
0 missing
att_10numeric10 unique values
0 missing
att_11numeric10 unique values
0 missing
att_12numeric10 unique values
0 missing
att_13numeric8 unique values
0 missing
att_14numeric10 unique values
0 missing
att_15numeric10 unique values
0 missing
att_16numeric10 unique values
0 missing
att_17numeric10 unique values
0 missing
att_18numeric10 unique values
0 missing
att_19numeric10 unique values
0 missing
att_20numeric10 unique values
0 missing
att_21numeric10 unique values
0 missing
att_22numeric10 unique values
0 missing
att_23numeric10 unique values
0 missing
att_24numeric10 unique values
0 missing
att_25numeric10 unique values
0 missing
att_26numeric10 unique values
0 missing
att_27numeric10 unique values
0 missing
att_28numeric10 unique values
0 missing
att_29numeric9 unique values
0 missing
att_30numeric9 unique values
0 missing
att_31numeric10 unique values
0 missing
att_32numeric10 unique values
0 missing
att_33numeric10 unique values
0 missing
att_34numeric10 unique values
0 missing
att_35numeric8 unique values
0 missing
att_36numeric8 unique values
0 missing
att_37numeric10 unique values
0 missing
att_38numeric10 unique values
0 missing
att_39numeric9 unique values
0 missing
att_40numeric10 unique values
0 missing
att_41numeric10 unique values
0 missing
att_42numeric10 unique values
0 missing
att_43numeric10 unique values
0 missing
att_44numeric10 unique values
0 missing
att_45numeric9 unique values
0 missing
att_46numeric10 unique values
0 missing
att_47numeric10 unique values
0 missing
att_48numeric10 unique values
0 missing
att_49numeric8 unique values
0 missing
att_50numeric4 unique values
0 missing
att_51numeric5 unique values
0 missing
att_52numeric3 unique values
0 missing
att_53numeric10 unique values
0 missing
att_54numeric8 unique values
0 missing
att_55numeric8 unique values
0 missing
att_56numeric9 unique values
0 missing
att_57numeric10 unique values
0 missing
att_58numeric10 unique values
0 missing
att_59numeric10 unique values
0 missing
att_60numeric10 unique values
0 missing
att_61numeric9 unique values
0 missing
att_62numeric10 unique values
0 missing
att_63numeric10 unique values
0 missing
att_64numeric10 unique values
0 missing
att_65numeric10 unique values
0 missing
att_66numeric10 unique values
0 missing
att_67numeric9 unique values
0 missing
att_68numeric9 unique values
0 missing
att_69numeric10 unique values
0 missing
att_70numeric10 unique values
0 missing
att_71numeric10 unique values
0 missing
att_72numeric9 unique values
0 missing
att_73numeric10 unique values
0 missing
att_74numeric9 unique values
0 missing
att_75numeric9 unique values
0 missing
att_76numeric10 unique values
0 missing
att_77numeric9 unique values
0 missing
att_78numeric9 unique values
0 missing
att_79numeric9 unique values
0 missing
att_80numeric10 unique values
0 missing
att_81numeric10 unique values
0 missing
att_82numeric9 unique values
0 missing
att_83numeric9 unique values
0 missing
att_84numeric9 unique values
0 missing
att_85numeric9 unique values
0 missing
att_86numeric10 unique values
0 missing
att_87numeric9 unique values
0 missing
att_88numeric9 unique values
0 missing
att_89numeric9 unique values
0 missing
att_90numeric9 unique values
0 missing
att_91numeric10 unique values
0 missing
att_92numeric10 unique values
0 missing
att_93numeric9 unique values
0 missing
att_94numeric9 unique values
0 missing
att_95numeric9 unique values
0 missing
att_96numeric10 unique values
0 missing
att_97numeric9 unique values
0 missing
att_98numeric8 unique values
0 missing
att_99numeric7 unique values
0 missing
att_100numeric8 unique values
0 missing
att_101numeric9 unique values
0 missing
att_102numeric9 unique values
0 missing
att_103numeric8 unique values
0 missing
att_104numeric8 unique values
0 missing
att_105numeric9 unique values
0 missing
att_106numeric9 unique values
0 missing
att_107numeric10 unique values
0 missing
att_108numeric9 unique values
0 missing
att_109numeric7 unique values
0 missing
att_110numeric9 unique values
0 missing
att_111numeric9 unique values
0 missing
att_112numeric10 unique values
0 missing
att_113numeric7 unique values
0 missing
att_114numeric7 unique values
0 missing
att_115numeric8 unique values
0 missing
att_116numeric4 unique values
0 missing
att_117numeric9 unique values
0 missing
att_118numeric9 unique values
0 missing
att_119numeric8 unique values
0 missing
att_120numeric7 unique values
0 missing
att_121numeric8 unique values
0 missing
att_122numeric9 unique values
0 missing
att_123numeric9 unique values
0 missing
att_124numeric8 unique values
0 missing
att_125numeric8 unique values
0 missing
att_126numeric8 unique values
0 missing
att_127numeric9 unique values
0 missing
att_128numeric9 unique values
0 missing

107 properties

108000
Number of instances (rows) of the dataset.
129
Number of attributes (columns) of the dataset.
0
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.
129
Number of numeric attributes.
0
Number of nominal attributes.
0.43
First quartile of standard deviation of attributes of the numeric type.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
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
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
9.65
Mean skewness among attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
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
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
Percentage of instances belonging to the most frequent class.
3.21
Mean standard deviation of attributes of the numeric type.
53.22
Second quartile (Median) of kurtosis among attributes of the numeric type.
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
Entropy of the target attribute values.
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
0.19
Second quartile (Median) of means among attributes of the numeric type.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum entropy among attributes.
-1.3
Minimum kurtosis among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
806.47
Maximum kurtosis among attributes of the numeric type.
0.01
Minimum of means among attributes of the numeric type.
6.46
Second quartile (Median) of skewness among attributes of the numeric type.
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
499.5
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of binary attributes.
0.7
Second quartile (Median) of standard deviation of attributes of the numeric type.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0
Number of attributes divided by the number of instances.
Maximum mutual information between the nominal attributes and the target attribute.
The minimal number of distinct values among attributes of the nominal type.
-0.97
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
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.
The maximum number of distinct values among attributes of the nominal type.
0.32
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
269.91
Third quartile of kurtosis among attributes of the numeric type.
0.15
Average class difference between consecutive instances.
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
28.43
Maximum skewness among attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
100
Percentage of numeric attributes.
0.95
Third quartile of means among attributes of the numeric type.
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
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
288.68
Maximum standard deviation of attributes of the numeric type.
Number of instances belonging to the least frequent class.
0
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
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
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Average entropy of the attributes.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of entropy among attributes.
15.54
Third quartile of skewness among attributes of the numeric type.
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
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
189.78
Mean kurtosis among attributes of the numeric type.
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
3.31
First quartile of kurtosis among attributes of the numeric type.
1.6
Third quartile of standard deviation of attributes of the numeric type.
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
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
4.56
Mean of means among attributes of the numeric type.
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.04
First quartile of means among attributes of the numeric type.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
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
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Average mutual information between the nominal attributes and the target attribute.
0
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
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
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
1.99
First quartile of skewness among attributes of the numeric type.
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
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
Standard deviation of the number of distinct values among attributes of the nominal type.
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
Average number of distinct values among the attributes of the nominal type.

18 tasks

0 runs - estimation_procedure: 33% Holdout set - target_feature: class
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
0 runs - estimation_procedure: Test on Training Data - evaluation_measure: predictive_accuracy - target_feature: class
0 runs - estimation_procedure: 5 times 2-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
0 runs - estimation_procedure: Custom 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
0 runs - estimation_procedure: 33% Holdout set - target_feature: class
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
Define a new task