Data
BNG(spambase)

BNG(spambase)

active ARFF Publicly available Visibility: public Uploaded 09-04-2014 by Jan van Rijn
0 likes downloaded by 4 people , 4 total downloads 0 issues 0 downvotes
Issue #Downvotes for this reason By


Loading wiki
Help us complete this description Edit

58 features

class (target)nominal2 unique values
0 missing
word_freq_makenominal3 unique values
0 missing
word_freq_addressnominal3 unique values
0 missing
word_freq_allnominal3 unique values
0 missing
word_freq_3dnominal3 unique values
0 missing
word_freq_ournominal3 unique values
0 missing
word_freq_overnominal3 unique values
0 missing
word_freq_removenominal3 unique values
0 missing
word_freq_internetnominal3 unique values
0 missing
word_freq_ordernominal3 unique values
0 missing
word_freq_mailnominal3 unique values
0 missing
word_freq_receivenominal3 unique values
0 missing
word_freq_willnominal3 unique values
0 missing
word_freq_peoplenominal3 unique values
0 missing
word_freq_reportnominal3 unique values
0 missing
word_freq_addressesnominal3 unique values
0 missing
word_freq_freenominal3 unique values
0 missing
word_freq_businessnominal3 unique values
0 missing
word_freq_emailnominal3 unique values
0 missing
word_freq_younominal3 unique values
0 missing
word_freq_creditnominal3 unique values
0 missing
word_freq_yournominal3 unique values
0 missing
word_freq_fontnominal3 unique values
0 missing
word_freq_000nominal3 unique values
0 missing
word_freq_moneynominal3 unique values
0 missing
word_freq_hpnominal3 unique values
0 missing
word_freq_hplnominal3 unique values
0 missing
word_freq_georgenominal3 unique values
0 missing
word_freq_650nominal3 unique values
0 missing
word_freq_labnominal3 unique values
0 missing
word_freq_labsnominal3 unique values
0 missing
word_freq_telnetnominal3 unique values
0 missing
word_freq_857nominal3 unique values
0 missing
word_freq_datanominal3 unique values
0 missing
word_freq_415nominal3 unique values
0 missing
word_freq_85nominal3 unique values
0 missing
word_freq_technologynominal3 unique values
0 missing
word_freq_1999nominal3 unique values
0 missing
word_freq_partsnominal3 unique values
0 missing
word_freq_pmnominal3 unique values
0 missing
word_freq_directnominal3 unique values
0 missing
word_freq_csnominal3 unique values
0 missing
word_freq_meetingnominal3 unique values
0 missing
word_freq_originalnominal3 unique values
0 missing
word_freq_projectnominal3 unique values
0 missing
word_freq_renominal3 unique values
0 missing
word_freq_edunominal3 unique values
0 missing
word_freq_tablenominal3 unique values
0 missing
word_freq_conferencenominal3 unique values
0 missing
char_freq_%3Bnominal3 unique values
0 missing
char_freq_%28nominal3 unique values
0 missing
char_freq_%5Bnominal3 unique values
0 missing
char_freq_%21nominal3 unique values
0 missing
char_freq_%24nominal3 unique values
0 missing
char_freq_%23nominal3 unique values
0 missing
capital_run_length_averagenominal3 unique values
0 missing
capital_run_length_longestnominal3 unique values
0 missing
capital_run_length_totalnominal3 unique values
0 missing

107 properties

1000000
Number of instances (rows) of the dataset.
58
Number of attributes (columns) of the dataset.
2
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.
0
Number of numeric attributes.
58
Number of nominal attributes.
21.67
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
1
Number of binary attributes.
0
First quartile of mutual information between the nominal attributes and the target attribute.
0.33
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.17
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
0.19
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.66
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
2.98
Average number of distinct values among the attributes of the nominal type.
First quartile of skewness among attributes of the numeric type.
0.2
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.64
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
0.13
Standard deviation of the number of distinct values among attributes of the nominal type.
0.33
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
Mean skewness among attributes of the numeric type.
First quartile of standard deviation of attributes of the numeric type.
0.67
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.34
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
0.67
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.2
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
Mean standard deviation of attributes of the numeric type.
0.04
Second quartile (Median) of entropy among attributes.
0.33
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.17
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
0.33
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
60.59
Percentage of instances belonging to the most frequent class.
0.01
Minimal entropy among attributes.
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.2
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.97
Entropy of the target attribute values.
0.19
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
605948
Number of instances belonging to the most frequent class.
Minimum kurtosis among attributes of the numeric type.
Second quartile (Median) of means among attributes of the numeric type.
0.67
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.52
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
0.22
Maximum entropy among attributes.
Minimum of means among attributes of the numeric type.
0
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.33
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.39
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum kurtosis among attributes of the numeric type.
0
Minimal mutual information between the nominal attributes and the target attribute.
Second quartile (Median) of skewness among attributes of the numeric type.
0.2
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum of means among attributes of the numeric type.
2
The minimal number of distinct values among attributes of the nominal type.
1.72
Percentage of binary attributes.
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.67
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.
0.02
Maximum mutual information between the nominal attributes and the target attribute.
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
0.09
Third quartile of entropy among attributes.
0.33
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
351.88
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
3
The maximum number of distinct values among attributes of the nominal type.
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
Third quartile of kurtosis among attributes of the numeric type.
0.52
Average class difference between consecutive instances.
0.19
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.66
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Maximum skewness among attributes of the numeric type.
39.41
Percentage of instances belonging to the least frequent class.
0
Percentage of numeric attributes.
Third quartile of means among attributes of the numeric type.
0.64
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
0.67
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.33
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Maximum standard deviation of attributes of the numeric type.
394052
Number of instances belonging to the least frequent class.
100
Percentage of nominal attributes.
0
Third quartile of mutual information between the nominal attributes and the target attribute.
0.34
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
0.33
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.2
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
0.06
Average entropy of the attributes.
0.67
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.02
First quartile of entropy among attributes.
Third quartile of skewness among attributes of the numeric type.
0.17
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
0.19
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.66
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Mean kurtosis among attributes of the numeric type.
0.33
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of kurtosis among attributes of the numeric type.
Third quartile of standard deviation of attributes of the numeric type.
0.64
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
0.67
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.33
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Mean of means among attributes of the numeric type.
0
Average mutual information between the nominal attributes and the target attribute.
0.19
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of means among attributes of the numeric type.
0.67
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.34
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
0.33
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.2
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001

13 tasks

5 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
0 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: class
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - 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: 10-fold Crossvalidation - evaluation_measure: precision - target_feature: class
0 runs - estimation_procedure: 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
214 runs - estimation_procedure: Interleaved Test then Train - target_feature: class
Define a new task