spambase_reproduced
OpenML dataset with id 44095
Author name not available (Why is that?)
Full work available at URL: https://api.openml.org/data/v1/download/22103191/spambase_reproduced.arff
Upload date: 21 June 2022
Dataset Characteristics
Number of classes: 2
Number of features: 58 (numeric: 57, symbolic: 1 and in total binary: 1 )
Number of instances: 4,601
Number of instances with missing values: 0
Number of missing values: 0
Author: Mark Hopkins, Erik Reeber, George Forman, Jaap Suermondt
Source: UCI
Please cite: UCI
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.
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