bayes classifier example

This series of articles is edited by cloud Twilight. Please indicate the source for reprinting. Http://blog.csdn.net/lyunduanmuxue/article/details/20068781 Thank you for your cooperation! Today we will introduce a simple and efficient classifier, Naive Bayes classifier ). I believe that those who have learned probability theory should not be unfamiliar with the

Bayesian classifierThe classification principle of Bayesian classifier is based on the prior probability of an object, and the Bayesian formula is used to calculate the posteriori probability, that is, the probability of the object belonging to a certain class, and select the class with the maximum posteriori probability as the class to which the object belongs. At present, there are four kinds of Bayesian classifiers, each of which are: Naive

Bayesian classifierThe classification principle of Bayesian classifier is based on the prior probability of an object, and the Bayesian formula is used to calculate the posteriori probability, that is, the probability of the object belonging to a certain class, and select the class with the maximum posteriori probability as the class to which the object belongs. At present, there are four kinds of Bayesian classifiers, each of which are: Naive

Implementation of naive Bayes classifier (php) this article uses php to implement a naive Bayes classifier, which classifies records of discrete variables with discrete attribute values .? After learning the data in the sample.csvfile, the classification model is used to predict the class indexes of the data in predict

the document model, the Class-condition probability must also be calculated in the document model, and vice versa. In order to avoid the probability result of class conditions being 0, Laplace probability estimation is adopted. Preprocessing of the training database To improve the classification efficiency and accuracy, the training database must be preprocessed. The main preprocessing steps are as follows: Read all training texts under a certain category Perform word segmentation for thes

1 #examples of linear and nonlinear classifiers in cs231n (Softmax)2 #Note that the calculation of the inverse propagation3 4 #-*-coding:utf-8-*-5 ImportNumPy as NP6 ImportMatplotlib.pyplot as Plt7N = 100#Number of points per class8D = 2#dimensionality9K = 3#Number of classesTenX = Np.zeros ((n*k,d))#data Matrix (each row = Single example) Oney = Np.zeros (n*k, dtype='uint8')#Class Labels A forJinchxrange (K): -IX = Range (n*j,n* (j+1)) -R = Np.linsp

Example of Naive Bayes algorithm and Bayesian exampleApplication of Bayesian The famous application of Bayesian classifier for spam filtering is spam filtering, if you want to learn more about this, you can go to hacker and painter or the corresponding chapter in the beauty of mathematics. For the basic implementation of Bayesian, see the dataset in two folders

probability of B. Bayesian FormulaBayesian formula provides a method to calculate the posterior probability P (B | A) from the prior probability P (A), P (B), and P (A | B ). Bayesian theorem is based on the following Bayesian formula: P (A | B) increases with the growth of P (A) and P (B | A), and decreases with the growth of P (B, that is, if B is more likely to be observed when it is independent of A, then B's support for a is smaller. Naive Bayes