10 article recommendations on naive Bayes

This paper mainly introduces the knowledge of how to use naive Bayesian algorithm in Python. Has a good reference value. Let's take a look at the little part here. Why the title is "using" instead of "implementing": First, the pros provide algorithms that are higher than the algorithms we write ourselves, both in terms of efficiency and accuracy. Secondly, for those who are not good at maths, it is very painful to study a bunch of formulas in order to realize the algorithm. Again, there is no need to "reinvent the wheel" unless the algorithms provided by others meet their own needs. Below the point, do not know the Bayesian algorithm can go to check the relevant information, here is just a brief introduction: 1. Bayesian formula: P (a| b) =p (AB)/P (b) 2. Bayesian Inference: P (a| B) =p (A) XP (b| A)/P (B) expressed in words: posterior probability = priori probability x Similarity/Normalization constants The problem that the Bayesian algorithm solves is how to find the similarity, namely: P (b| A) has a value of 3. Three commonly used naive Bayes algorithms are provided in the Scikit-learn package,

1. Details how to use Naive Bayes algorithm in Python

Introduction: This article mainly introduces how to use the naïve Bayesian algorithm in Python knowledge. Has a good reference value. Let's take a look at the little series.

2. Introduction to how to use the naive Bayesian algorithm in Python

Introduction: This article explains how to use the naive Bayesian algorithm in Python

3. Python implementation of naive Bayesian algorithm

Summary: Advantages and disadvantages of the algorithm: it is still effective in the case of less data, and can handle the disadvantages of multiple categories of problems: how to prepare for input data sensitive data types: the idea of the nominal data algorithm

4. Python implementation of naive Bayesian algorithm

Introduction: Python implementation of naive Bayesian algorithm

5. Naive Bayes (naive Bayesian algorithm) [Classification algorithm],naivebayes_php tutorial

Introduction: Naive Bayes (naive Bayesian algorithm) [classification algorithm],naivebayes. Naive Bayes (naive Bayesian algorithm) [classification algorithm],naivebayes Nave Bayes (naive Bayesian) classification algorithm implementation (1) Introduction: (2) algorithm Description: (3) 1? PHP 2/* 3 *naive Bayes Plain

6. Implementation of the Plain Bayesian classifier (PHP)

Introduction: Implementation of naive Bayesian classifier (PHP) This paper implements a naive Bayesian classifier with PHP, which is used for the Bayesian classification of the records with the attribute values as discrete variables. By studying the data in the Sample.csv file, the classification model is obtained, and then the class index of the data in the Predict.csv is predicted. For each predicted data, calculate the probability of belonging to each class, and then the class with the greatest probability is the class attribution to which the data is predicted. The attachment contains the program text

7. Implementation of the Plain Bayesian classifier (PHP)

Introduction: Implementation of naive Bayesian classifier (PHP) This paper implements a naive Bayesian classifier with PHP, which is used for the Bayesian classification of the records with the attribute values as discrete variables. By studying the data in the Sample.csv file, the classification model is obtained, and then the class index of the data in the Predict.csv is predicted. For each predicted data, calculate the probability of belonging to each class, and then the class with the greatest probability is the class attribution to which the data is predicted. The attachment contains the program file: Bys.

8. Naive Bayes (naive Bayesian algorithm) [Classification algorithm],naivebayes

Introduction: Naive Bayes (naive Bayesian algorithm) [classification algorithm],naivebayes. Naive Bayes (naive Bayesian algorithm) [classification algorithm],naivebayes Nave Bayes (naive Bayesian) classification algorithm implementation (1) Introduction: (2) algorithm Description: (3) 1? PHP 2/* 3 *naive Bayes Plain

9. A tutorial on machine learning using Python to implement a Bayesian classifier from zero

Introduction: This article mainly introduces the use of Python from the zero implementation of the Bayesian classifier tutorial, naive Bayesian algorithm belongs to the basic content of machine learning, practical and efficient, this article shows in detail the implementation of the Python language steps, the need for friends can refer to the next

10. Application of naive Bayesian algorithm in spam filtering

Introduction: Since I recently wrote a paper on the classification of Big Data (spat: The tutor is urging every day), I borrowed a few books about big data in the library. Today, "New Internet Big Data Mining" (interesting to see) mentioned spam filtering, let me think of yesterday in the 1280 community saw a famous enterprise interview, "in the game real-time communication,