enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  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. Bayes error rate - Wikipedia

    en.wikipedia.org/wiki/Bayes_error_rate

    This solution is known as the Bayes classifier. ... Naive Bayes classifier; References This page ... Statistics; Cookie statement ...

  5. 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

  6. Training, validation, and test data sets - Wikipedia

    en.wikipedia.org/wiki/Training,_validation,_and...

    A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]

  7. Bayesian classifier - Wikipedia

    en.wikipedia.org/wiki/Bayesian_classifier

    In computer science and statistics, Bayesian classifier may refer to: any classifier based on Bayesian probability; a Bayes classifier, one that always chooses the class of highest posterior probability in case this posterior distribution is modelled by assuming the observables are independent, it is a naive Bayes classifier

  8. Bayesian statistics - Wikipedia

    en.wikipedia.org/wiki/Bayesian_statistics

    Bayesian statistics (/ ˈ b eɪ z i ə n / BAY-zee-ən or / ˈ b eɪ ʒ ən / BAY-zhən) [1] is a theory in the field of statistics based on the Bayesian interpretation of probability, where probability expresses a degree of belief in an event. The degree of belief may be based on prior knowledge about the event, such as the results of previous ...

  9. Classification rule - Wikipedia

    en.wikipedia.org/wiki/Classification_rule

    The bayes classifier is the classifier which assigns classes optimally based on the known attributes (i.e. features or regressors) of the elements to be classified. A special kind of classification rule is binary classification, for problems in which there are only two classes.