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  2. List of datasets for machine-learning research - Wikipedia

    en.wikipedia.org/wiki/List_of_datasets_for...

    Ling-Spam Dataset Corpus containing both legitimate and spam emails. Four version of the corpus involving whether or not a lemmatiser or stop-list was enabled. 2,412 Ham 481 Spam Text Classification 2000 [38] [39] Androutsopoulos, J. et al. SMS Spam Collection Dataset Collected SMS spam messages. None. 5,574 Text Classification 2011 [40] [41]

  3. Enron Corpus - Wikipedia

    en.wikipedia.org/wiki/Enron_Corpus

    A visualization of the email network in the Enron Corpus, with coloring representing eight communities. The corpus is valued as one of the few publicly available mass collections of real emails easily available for study; such collections are typically bound by numerous privacy and legal restrictions which render them prohibitively difficult to access, such as non-disclosure agreements and ...

  4. Kaggle - Wikipedia

    en.wikipedia.org/wiki/Kaggle

    Kaggle is a data science competition platform and online community for data scientists and machine learning practitioners under Google LLC.Kaggle enables users to find and publish datasets, explore and build models in a web-based data science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges.

  5. Naive Bayes spam filtering - Wikipedia

    en.wikipedia.org/wiki/Naive_Bayes_spam_filtering

    For these approximations to make sense, the set of learned messages needs to be big and representative enough. It is also advisable that the learned set of messages conforms to the 50% hypothesis about repartition between spam and ham, i.e. that the datasets of spam and ham are of same size. [8]

  6. Bag-of-words model - Wikipedia

    en.wikipedia.org/wiki/Bag-of-words_model

    The bag-of-words model is commonly used in methods of document classification where, for example, the (frequency of) occurrence of each word is used as a feature for training a classifier. [1] It has also been used for computer vision .

  7. The Spamhaus Project - Wikipedia

    en.wikipedia.org/wiki/The_Spamhaus_Project

    The Combined Spam Sources (CSS) [12] is an automatically produced dataset of IP addresses that are involved in sending low-reputation email. Listings can be based on HELO greetings without an A record, generic looking rDNS or use of fake domains, which could indicate spambots or server misconfiguration.

  8. Email spam - Wikipedia

    en.wikipedia.org/wiki/Email_spam

    An email box folder filled with spam messages.. Email spam, also referred to as junk email, spam mail, or simply spam, is unsolicited messages sent in bulk by email ().The name comes from a Monty Python sketch in which the name of the canned pork product Spam is ubiquitous, unavoidable, and repetitive. [1]

  9. Apache SpamAssassin - Wikipedia

    en.wikipedia.org/wiki/Apache_SpamAssassin

    Apache SpamAssassin is a Perl-based application (Mail::SpamAssassin in CPAN) which is usually used to filter all incoming mail for one or several users.It can be run as a standalone application or as a subprogram of another application (such as a Milter, SA-Exim, Exiscan, MailScanner, MIMEDefang, Amavis) or as a client (spamc) that communicates with a daemon (spamd).