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GMM模型和贝叶斯分类器 用于视频图像的处理-GMM model and the Bayesian classifier for video image processing
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贝叶斯分类器的分类原理是通过某对象的先验概率，利用贝叶斯公式计算出其后验概率，即该对象属于某一类的概率，选择具有最大后验概率的类作为该对象所属的类-Bayesian classifier principle a priori probability of the object using the Bayesian formula to calculate the subsequent posterior probability that the object belongs to a certa
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朴素贝叶斯分类器在符号型数据库上的实现，这里说的符号型数据库指属性取值满足离散、无序、有限，无运算-bayesian classifier
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贝叶斯分类器的2分类的实现演示，随机生成数据，进行2维特征的2分类-Classification Bayesian classifier achieve demo, randomly generated data, 2-dimensional feature classification
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最小错误率贝叶斯决策 模式识别 贝叶斯分类器设计-Minimum error rate Bayesian decision pattern recognition Bayesian classifier design
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朴素贝叶斯分类器程序代码
采用朴素贝叶斯分类器算法，使用C++语言对英文文本进行分类，实现了一个文本分类器功能-Naive Bayesian classifier program code using Bayesian classification algorithm, using C++ language English text classification, to achieve a text classification function
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贝叶斯分类器-Bayesian classifier ..........
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matlab基于最小错误率的贝叶斯分类器设计-Bayesian classifier design matlab minimum error rate
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贝叶斯分类器，对两组数据实现分类判别，并计算判别的正确率-Bayesian classifier, to achieve the two sets of data classification and discrimination, and to calculate the correct rate of discrimination
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贝叶斯分类器:贝叶斯分类的基础是概率推理，就是在各种条件的存在不确定，仅知其出现概率的情况下，如何完成推理和决策任务。-Bayesian classifier
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bayesin classifier estimation program using matlab
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Comparison of Bayesian classifier
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其中贝叶斯分类包括最小错误率和最小风险两种
新手看看吧。也不错的-Bayesian classifier which comprises a minimum error rate and minimum risk two kinds novice to see it. Not bad
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根据贝叶斯的相关理论实现一个贝叶斯分类器，主要是分两个步骤：
1、产生数据，这里的数据是自己产生的，可以用自己需要分类的数据去替换
2、分类-According to Bayesian theory achieve a Bayesian classifier, mainly in two steps: 1, to generate the data, where the data is self-generated, you can use the classified data the
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bayesian classifier used to classify data using existing training data set, for example we can find whether client is bank defaulter or not using existing data set
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模式识别中应用的贝叶斯分类器 可以用于分类IRIS数据-Application of pattern recognition Bayesian classifier can be used to classify IRIS data
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A Bayesian classifier for pattern recognition
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A Bayesian classifier for pattern recognition
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本内容是有关机器学习的包含贝叶斯分类器，随机森林，支持向量机，神经网络，logistic多元回归等(The contents of this paper are machine learning, including Bayesian classifier, random forest, support vector machines, neural network, logistic multiple regression and so on)
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This toolbox contains programs for the multi-label classifier which explicitly exploits label dependency with Bayesian network structure.
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