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spambase

active ARFF Publicly available Visibility: public Uploaded 06-04-2014 by Jan van Rijn
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  • study_14 study_1 study_849 study_1074
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58 features

class (target)nominal2 unique values
0 missing
word_freq_makenumeric142 unique values
0 missing
word_freq_addressnumeric171 unique values
0 missing
word_freq_allnumeric214 unique values
0 missing
word_freq_3dnumeric43 unique values
0 missing
word_freq_ournumeric255 unique values
0 missing
word_freq_overnumeric141 unique values
0 missing
word_freq_removenumeric173 unique values
0 missing
word_freq_internetnumeric170 unique values
0 missing
word_freq_ordernumeric144 unique values
0 missing
word_freq_mailnumeric245 unique values
0 missing
word_freq_receivenumeric113 unique values
0 missing
word_freq_willnumeric316 unique values
0 missing
word_freq_peoplenumeric158 unique values
0 missing
word_freq_reportnumeric133 unique values
0 missing
word_freq_addressesnumeric118 unique values
0 missing
word_freq_freenumeric253 unique values
0 missing
word_freq_businessnumeric197 unique values
0 missing
word_freq_emailnumeric229 unique values
0 missing
word_freq_younumeric575 unique values
0 missing
word_freq_creditnumeric148 unique values
0 missing
word_freq_yournumeric401 unique values
0 missing
word_freq_fontnumeric99 unique values
0 missing
word_freq_000numeric164 unique values
0 missing
word_freq_moneynumeric143 unique values
0 missing
word_freq_hpnumeric395 unique values
0 missing
word_freq_hplnumeric281 unique values
0 missing
word_freq_georgenumeric240 unique values
0 missing
word_freq_650numeric200 unique values
0 missing
word_freq_labnumeric156 unique values
0 missing
word_freq_labsnumeric179 unique values
0 missing
word_freq_telnetnumeric128 unique values
0 missing
word_freq_857numeric106 unique values
0 missing
word_freq_datanumeric184 unique values
0 missing
word_freq_415numeric110 unique values
0 missing
word_freq_85numeric177 unique values
0 missing
word_freq_technologynumeric159 unique values
0 missing
word_freq_1999numeric188 unique values
0 missing
word_freq_partsnumeric53 unique values
0 missing
word_freq_pmnumeric163 unique values
0 missing
word_freq_directnumeric125 unique values
0 missing
word_freq_csnumeric108 unique values
0 missing
word_freq_meetingnumeric186 unique values
0 missing
word_freq_originalnumeric136 unique values
0 missing
word_freq_projectnumeric160 unique values
0 missing
word_freq_renumeric230 unique values
0 missing
word_freq_edunumeric227 unique values
0 missing
word_freq_tablenumeric38 unique values
0 missing
word_freq_conferencenumeric106 unique values
0 missing
char_freq_%3Bnumeric313 unique values
0 missing
char_freq_%28numeric641 unique values
0 missing
char_freq_%5Bnumeric225 unique values
0 missing
char_freq_%21numeric964 unique values
0 missing
char_freq_%24numeric504 unique values
0 missing
char_freq_%23numeric316 unique values
0 missing
capital_run_length_averagenumeric2161 unique values
0 missing
capital_run_length_longestnumeric271 unique values
0 missing
capital_run_length_totalnumeric919 unique values
0 missing

107 properties

4601
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.
57
Number of numeric attributes.
1
Number of nominal attributes.
Second quartile (Median) of entropy among attributes.
0.1
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.82
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
0.11
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
60.6
Percentage of instances belonging to the most frequent class.
15.19
Mean standard deviation of attributes of the numeric type.
127.38
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.78
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.97
Entropy of the target attribute values.
0.78
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
2788
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
0.1
Second quartile (Median) of means among attributes of the numeric type.
0.94
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.79
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum entropy among attributes.
5.26
Minimum kurtosis among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.1
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.21
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
1480.64
Maximum kurtosis among attributes of the numeric type.
0.01
Minimum of means among attributes of the numeric type.
9.72
Second quartile (Median) of skewness among attributes of the numeric type.
0.78
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.55
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
283.29
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
1.72
Percentage of binary attributes.
0.44
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.89
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.01
Number of attributes divided by the number of instances.
Maximum mutual information between the nominal attributes and the target attribute.
2
The minimal number of distinct values among attributes of the nominal type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
0.1
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.
2
The maximum number of distinct values among attributes of the nominal type.
1.59
Minimum skewness among attributes of the numeric type.
0
Percentage of missing values.
299.07
Third quartile of kurtosis among attributes of the numeric type.
1
Average class difference between consecutive instances.
0.78
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.92
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
31.06
Maximum skewness among attributes of the numeric type.
0.08
Minimum standard deviation of attributes of the numeric type.
98.28
Percentage of numeric attributes.
0.24
Third quartile of means among attributes of the numeric type.
0.94
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
0.89
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.08
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
606.35
Maximum standard deviation of attributes of the numeric type.
39.4
Percentage of instances belonging to the least frequent class.
1.72
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
0.09
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
0.1
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.82
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Average entropy of the attributes.
1813
Number of instances belonging to the least frequent class.
First quartile of entropy among attributes.
13.65
Third quartile of skewness among attributes of the numeric type.
0.82
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
0.78
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.92
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
241.17
Mean kurtosis among attributes of the numeric type.
0.94
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.2
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
50.66
First quartile of kurtosis among attributes of the numeric type.
0.84
Third quartile of standard deviation of attributes of the numeric type.
0.94
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
0.89
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.08
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
6.15
Mean of means among attributes of the numeric type.
0.61
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.06
First quartile of means among attributes of the numeric type.
0.94
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.09
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
0.1
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.82
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Average mutual information between the nominal attributes and the target attribute.
1
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
0.1
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.82
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
0.78
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.92
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.
5.85
First quartile of skewness among attributes of the numeric type.
0.78
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.94
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.
0.08
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
2
Average number of distinct values among the attributes of the nominal type.
0.32
First quartile of standard deviation of attributes of the numeric type.
0.94
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.09
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
0.89
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.82
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
11.19
Mean skewness among attributes of the numeric type.

11 tasks

0 runs - estimation_procedure: Test on Training Data - target_feature: class
0 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: class
0 runs - estimation_procedure: 5 times 2-fold Crossvalidation - target_feature: class
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - target_feature: class
0 runs - estimation_procedure: Leave one out - target_feature: class
0 runs - estimation_procedure: 10% Holdout set - target_feature: class
0 runs - estimation_procedure: 20% Holdout (Ordered) - target_feature: class
0 runs - estimation_procedure: 33% Holdout set - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10 times 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: class
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