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spambase_reproduced

spambase_reproduced

active ARFF Publicly available Visibility: public Uploaded 21-06-2022 by Perry
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Author: Mark Hopkins, Erik Reeber, George Forman, Jaap Suermondt Source: [UCI](https://archive.ics.uci.edu/ml/datasets/spambase) Please cite: [UCI](https://archive.ics.uci.edu/ml/citation_policy.html) SPAM E-mail Database The "spam" concept is diverse: advertisements for products/websites, make money fast schemes, chain letters, pornography... Our collection of spam e-mails came from our postmaster and individuals who had filed spam. Our collection of non-spam e-mails came from filed work and personal e-mails, and hence the word 'george' and the area code '650' are indicators of non-spam. These are useful when constructing a personalized spam filter. One would either have to blind such non-spam indicators or get a very wide collection of non-spam to generate a general purpose spam filter. For background on spam: Cranor, Lorrie F., LaMacchia, Brian A. Spam! Communications of the ACM, 41(8):74-83, 1998. ### Attribute Information: The last column denotes whether the e-mail was considered spam (1) or not (0), i.e. unsolicited commercial e-mail. Most of the attributes indicate whether a particular word or character was frequently occurring in the e-mail. The run-length attributes (55-57) measure the length of sequences of consecutive capital letters. For the statistical measures of each attribute, see the end of this file. Here are the definitions of the attributes: 48 continuous real [0,100] attributes of type word_freq_WORD = percentage of words in the e-mail that match WORD, i.e. 100 * (number of times the WORD appears in the e-mail) / total number of words in e-mail. A "word" in this case is any string of alphanumeric characters bounded by non-alphanumeric characters or end-of-string. 6 continuous real [0,100] attributes of type char_freq_CHAR = percentage of characters in the e-mail that match CHAR, i.e. 100 * (number of CHAR occurences) / total characters in e-mail 1 continuous real [1,...] attribute of type capital_run_length_average = average length of uninterrupted sequences of capital letters 1 continuous integer [1,...] attribute of type capital_run_length_longest = length of longest uninterrupted sequence of capital letters 1 continuous integer [1,...] attribute of type capital_run_length_total = sum of length of uninterrupted sequences of capital letters = total number of capital letters in the e-mail 1 nominal {0,1} class attribute of type spam = denotes whether the e-mail was considered spam (1) or not (0), i.e. unsolicited commercial e-mail.

58 features

class (target)nominal2 unique values
0 missing
word_freq_telnetnumeric128 unique values
0 missing
word_freq_labsnumeric179 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
word_freq_freenumeric253 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_makenumeric142 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
Show all 58 features

19 properties

NumberOfInstances
4601
Number of instances (rows) of the dataset.
NumberOfFeatures
58
Number of attributes (columns) of the dataset.
NumberOfClasses
2
Number of distinct values of the target attribute (if it is nominal).
NumberOfMissingValues
0
Number of missing values in the dataset.
NumberOfInstancesWithMissingValues
0
Number of instances with at least one value missing.
NumberOfNumericFeatures
57
Number of numeric attributes.
NumberOfSymbolicFeatures
1
Number of nominal attributes.
PercentageOfSymbolicFeatures
1.72
Percentage of nominal attributes.
AutoCorrelation
1
Average class difference between consecutive instances.
PercentageOfNumericFeatures
98.28
Percentage of numeric attributes.
PercentageOfMissingValues
0
Percentage of missing values.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
PercentageOfBinaryFeatures
1.72
Percentage of binary attributes.
NumberOfBinaryFeatures
1
Number of binary attributes.
MinorityClassSize
1813
Number of instances belonging to the least frequent class.
MinorityClassPercentage
39.4
Percentage of instances belonging to the least frequent class.
MajorityClassSize
2788
Number of instances belonging to the most frequent class.
MajorityClassPercentage
60.6
Percentage of instances belonging to the most frequent class.
Dimensionality
0.01
Number of attributes divided by the number of instances.
Show all 19 properties

2 tasks

Supervised Classification on spambase_reproduced
0 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: class
Supervised Classification on spambase_reproduced
0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
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