naive bayes classification

Transferred from: http://www.letiantian.me/2014-10-12-three-models-of-naive-nayes/Naive Bayesian is a very good classifier, in the use of naive Bayesian classifier to divide the message there is a simple introduction to naive Bayesian.If a sample has n characteristics, denoted by [latex]x_{1},x_{2},..., X_{n}[/latex],

). When sorting, an example of X is given, and all of the P (y|x) is found in a pile of posteriori probabilities, the largest of which is the category x belongs to. According to the Bayesian formula, the posterior probability is P (y| X) =p (x| y) P (Y) p (X) When comparing the posteriori probabilities of different Y-values, the denominator p (X) is always constant, so it can be ignored . The priori probability P (Y) can be easily estimated by calculating the proportion of training samples that

Classification algorithm pay attention to the beginning algorithm to find the probability characteristic parameter of the prior probability condition the continuous mean of the discrete characteristic parameter and the standard deviation to find the probability of conditional probabilities based on mean and standard deviation Naive Bayesian algorithm is a classificatio