Naive Bayes Classifier

A naive Bayes classifier is a simple probabilistic classifier based on applying Bayes' theorem with strong (naive) independence assumptions. A more descriptive term for the underlying probability model would be "independent feature model".

Read more about Naive Bayes ClassifierIntroduction, The Naive Bayes Probabilistic Model, Parameter Estimation, Sample Correction, Constructing A Classifier From The Probability Model, Discussion

Other articles related to "naive bayes classifier, classifier, bayes, naive bayes, naive":

Random Naive Bayes - Naive Bayes Classifier
... The naive Bayes classifier is a probabilistic classifier simplifying Bayes' theorem by naively assuming class conditional independence ... leads to biased posterior probabilities, the ordered probabilities of Naive Bayes result in a classification performance comparable to that of ... Notwithstanding Naive Bayes' popularity due to its simplicity combined with high accuracy and speed, its conditional independence assumption rarely holds ...
Naive Bayes Classifier - Examples - Document Classification
... Here is a worked example of naive Bayesian classification to the document classification problem ... relation to other words, or other document-context.) Now by definition and Bayes' theorem manipulates these into a statement of probability in terms of ...

Famous quotes containing the word naive:

    Cynicism is full of naive disappointments.
    Mason Cooley (b. 1927)