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  2. Naive Bayes classifier - Wikipedia

    en.wikipedia.org/wiki/Naive_Bayes_classifier

    Example of a naive Bayes classifier depicted as a Bayesian Network. In statistics, naive Bayes classifiers are a family of linear "probabilistic classifiers" which assumes that the features are conditionally independent, given the target class. The strength (naivety) of this assumption is what gives the classifier its name.

  3. Bayes classifier - Wikipedia

    en.wikipedia.org/wiki/Bayes_classifier

    In statistical classification, the Bayes classifier is the classifier having the smallest probability of misclassification of all classifiers using the same set of features. [ 1 ] Definition

  4. KH Coder - Wikipedia

    en.wikipedia.org/wiki/KH_Coder

    Word frequency statistics, part-of-speech analysis, grouping, correlation analysis, and visualization (including histograms and clustering maps) are among the features offered by KH Coder. [ 2 ] It is well received by researchers worldwide and used in a large number of disciplines, including neuroscience , sociology , psychology , public health ...

  5. Bag-of-words model in computer vision - Wikipedia

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

    The simplest one is Naive Bayes classifier. [2] Using the language of graphical models, the Naive Bayes classifier is described by the equation below. The basic idea (or assumption) of this model is that each category has its own distribution over the codebooks, and that the distributions of each category are observably different.

  6. Additive smoothing - Wikipedia

    en.wikipedia.org/wiki/Additive_smoothing

    Classification. Additive smoothing is commonly a component of naive Bayes classifiers. Statistical language modelling In a bag of ...

  7. Probabilistic classification - Wikipedia

    en.wikipedia.org/wiki/Probabilistic_classification

    Binary probabilistic classifiers are also called binary regression models in statistics. In econometrics, probabilistic classification in general is called discrete choice. Some classification models, such as naive Bayes, logistic regression and multilayer perceptrons (when trained under an appropriate loss function) are

  8. Bayes error rate - Wikipedia

    en.wikipedia.org/wiki/Bayes_error_rate

    Naive Bayes classifier; References This page was last edited on 17 December 2024, at 03:38 (UTC). Text is available under the ...

  9. WordStat - Wikipedia

    en.wikipedia.org/wiki/WordStat

    Classification of documents using Naïve-Bayes or k-nearest neighbor algorithms applied either on words or concepts. Automatic topic extraction using first order (word co-occurrences) or second order (co-occurrence profiles) hierarchical clustering and multidimensional scaling. Topic modeling to extract the main themes using NNMF and Factor ...