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  2. Naive Bayes classifier - Wikipedia

    en.wikipedia.org/wiki/Naive_Bayes_classifier

    In the statistics literature, naive Bayes models are known under a variety of names, including simple Bayes and independence Bayes. [3] All these names reference the use of Bayes' theorem in the classifier's decision rule, but naive Bayes is not (necessarily) a Bayesian method.

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

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

    A 3.1 TB dataset consisting of permissively licensed source code in 30 programming languages. Filtered through license detection and deduplication. 6 TB, 51.76B files (prior to deduplication); 3 TB, 5.28B files (after). 358 programming languages. Parquet Language modeling, autocompletion, program synthesis. 2022 [402] [403]

  4. Naive Bayes spam filtering - Wikipedia

    en.wikipedia.org/wiki/Naive_Bayes_spam_filtering

    Naive Bayes spam filtering is a baseline technique for dealing with spam that can tailor itself to the email needs of individual users and give low false positive spam detection rates that are generally acceptable to users. It is one of the oldest ways of doing spam filtering, with roots in the 1990s.

  5. Bayes error rate - Wikipedia

    en.wikipedia.org/wiki/Bayes_error_rate

    Download QR code; Print/export Download as PDF; Printable version; In other projects ... Naive Bayes classifier; References This page was last edited on ...

  6. Bayesian programming - Wikipedia

    en.wikipedia.org/wiki/Bayesian_programming

    It can be drastically simplified by assuming that the probability of appearance of a word knowing the nature of the text (spam or not) is independent of the appearance of the other words. This is the naive Bayes assumption and this makes this spam filter a naive Bayes model. For instance, the programmer can assume that:

  7. Data mining - Wikipedia

    en.wikipedia.org/wiki/Data_mining

    Naive Bayes; Artificial neural networks; ... Public access to application source code is also available. ... An open-source machine learning library for the Python ...

  8. Recursive Bayesian estimation - Wikipedia

    en.wikipedia.org/wiki/Recursive_Bayesian_estimation

    A Bayes filter is an algorithm used in computer science for calculating the probabilities of multiple beliefs to allow a robot to infer its position and orientation. Essentially, Bayes filters allow robots to continuously update their most likely position within a coordinate system, based on the most recently acquired sensor data.

  9. Approximate Bayesian computation - Wikipedia

    en.wikipedia.org/wiki/Approximate_Bayesian...

    Engine for Likelihood-Free Inference. ELFI is a statistical software package written in Python for Approximate Bayesian Computation (ABC), also known e.g. as likelihood-free inference, simulator-based inference, approximative Bayesian inference etc. [83] ABCpy: Python package for ABC and other likelihood-free inference schemes.