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BNG(spambase)

BNG(spambase)

active ARFF Publicly available Visibility: public Uploaded 06-10-2016 by Jason
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58 features

class (target)nominal2 unique values
0 missing
word_freq_telnetnominal3 unique values
0 missing
word_freq_labsnominal3 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_semicolonnominal3 unique values
0 missing
char_freq_leftroundbracketnominal3 unique values
0 missing
char_freq_leftbracketnominal3 unique values
0 missing
char_freq_exclamationnominal3 unique values
0 missing
char_freq_dolarsignnominal3 unique values
0 missing
char_freq_doublequotesnominal3 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
word_freq_freenominal3 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_makenominal3 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

62 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.
0
First quartile of mutual information between the nominal attributes and the target attribute.
1.72
Percentage of binary attributes.
0
Percentage of instances having missing values.
0
Percentage of missing values.
0
Percentage of numeric attributes.
100
Percentage of nominal attributes.
0.02
First quartile of entropy among attributes.
First quartile of kurtosis among attributes of the numeric type.
First quartile of means among attributes of the numeric type.
0.13
Standard deviation of the number of distinct values among attributes of the nominal type.
First quartile of skewness among attributes of the numeric type.
First quartile of standard deviation of attributes of the numeric type.
0.04
Second quartile (Median) of entropy among attributes.
Second quartile (Median) of kurtosis among attributes of the numeric type.
Second quartile (Median) of means among attributes of the numeric type.
0
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Second quartile (Median) of skewness among attributes of the numeric type.
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.09
Third quartile of entropy among attributes.
Third quartile of kurtosis among attributes of the numeric type.
Third quartile of means among attributes of the numeric type.
0
Third quartile of mutual information between the nominal attributes and the target attribute.
Third quartile of skewness among attributes of the numeric type.
Third quartile of standard deviation of attributes of the numeric type.
0.52
Average class difference between consecutive instances.
Mean of means among attributes of the numeric type.
0.97
Entropy of the target attribute values.
0
Number of attributes divided by the number of instances.
351.88
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
60.59
Percentage of instances belonging to the most frequent class.
605948
Number of instances belonging to the most frequent class.
0.22
Maximum entropy among attributes.
Maximum kurtosis among attributes of the numeric type.
Maximum of means among attributes of the numeric type.
0.02
Maximum mutual information between the nominal attributes and the target attribute.
3
The maximum number of distinct values among attributes of the nominal type.
Maximum skewness among attributes of the numeric type.
Maximum standard deviation of attributes of the numeric type.
0.06
Average entropy of the attributes.
Mean kurtosis among attributes of the numeric type.
1
Number of binary attributes.
0
Average mutual information between the nominal attributes and the target attribute.
21.67
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
2.98
Average number of distinct values among the attributes of the nominal type.
Mean skewness among attributes of the numeric type.
Mean standard deviation of attributes of the numeric type.
0.01
Minimal entropy among attributes.
Minimum kurtosis among attributes of the numeric type.
Minimum of means among attributes of the numeric type.
0
Minimal mutual information between the nominal attributes and the target attribute.
2
The minimal number of distinct values among attributes of the nominal type.
Minimum skewness among attributes of the numeric type.
Minimum standard deviation of attributes of the numeric type.
39.41
Percentage of instances belonging to the least frequent class.
394052
Number of instances belonging to the least frequent class.

21 tasks

0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: precision - 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
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
98 runs - estimation_procedure: Interleaved Test then Train - 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
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