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beiyesifenleiqi
- 朴素贝叶斯分类器，对于连续变量情形，此算法将连续变量进行离散，分类效果较好-Naive Bayesian classifier, the continuous variable case, this algorithm for discrete variables, the classification results better
bp.example
- 采用动量梯度下降算法训练BP网络，采用两种训练方法，即 L-M 优化算法（trainlm）和贝叶斯正则化算法（trainbr），用以训练 BP 网络-Gradient descent algorithm using momentum BP network training, using two training methods, namely, LM optimization algorithm (trainlm) and Bayesian regularization algorithm (t
data-dig
- 一些数据挖掘算法相关,包含定义网络拓扑,有关高血压研究方面的数据,朴素贝叶斯分类,关联规则基本概念,数据挖掘算法, 决策树方法在数据挖掘中的应用,训练贝叶斯信念网络,后向传播,贝叶斯信念网络,后向传播和可解释性,多层前馈神经网络-Some relevant data mining algorithms, including the definition of network topology, the high blood pressure research data, Naive Baye
beiyesi
- 一个经典的贝叶斯算法，可以用在很多项目，也可以提供大家学习和参考-A classical Bayesian algorithm, can be used in a lot of projects, may also provide U.S. study and reference
NB
- 朴素贝叶斯算法，以函数形式实现，花了一个上午的时间-Naive Bayes algorithm, in order to function the form of implementation, a morning flower time
Bayesian_Classification
- 使用高斯模型对威斯康辛州大学医学院长期乳腺癌数据进行了贝叶斯模式识别。识别率为95以上，可以作为模式识别的重要案例。-Gaussian model using the University of Wisconsin School of Medicine conducted a long-term breast cancer data Bayesian pattern recognition. Recognition rate is above 95 can be regarded as an i
Bayes
- 该代码包是一个基于贝叶斯分类器的分类程序，内含数据集、可运行程序-The code package is a classifier based on Bayesian classification procedures, including data sets, can run the program
naivebayes
- 贝叶斯决策器，基于最小错误率的贝叶斯决算法-Bayesian decision-making, based on minimum error rate of Bayesian decision-making
11912873naivebayesclassificationbasedongenetic
- 贝叶斯网络分类器的一点小程序，也许有用，请各位资源下载-Bayesian Network Classifier for small procedures, may be useful, please download resources
beyes
- 详细介绍了贝叶斯公式在自动文本分类领域的使用，并且提到了关于互信息特征提取的方法。以及其分类的例子。-Bayesian formula described in detail in the field of automatic text categorization of the use of, and reference information on each feature extraction method. As well as examples of their classificat
bayesys
- 贝叶斯算法：盲分离技术，信号处理技术，信息论与编码-Bayesian
patternrecognition
- 文件中包含多种模式识别常用的算法，如：ISODATA、 K均值、 感知器、 LMSE最小误差、 贝叶斯，希望对大家能有所帮助-File contains a variety of commonly used pattern recognition algorithms, such as: ISODATA, K-means, perceptron, LMSE the smallest error, Bayesian, in the hope that we can help
BayesNetWorkMSBNx
- 数据挖掘中贝叶斯信念网络的软件，可进行描述与分类。-Data Mining of Bayesian belief networks in software, can be described and classified.
node
- 模拟网络通信，对其中的信息进行统计，用贝叶斯算法计算特定信息的后验概率，自动日志-Simulation of network communications, for which statistical information, using Bayesian algorithm-specific information on a posteriori probability, automatic log
facedetcer
- 基于贝叶斯理论的指纹识别算法及学习套件, 使用贝叶斯概率论实现对指纹识别,特征码提取,特征对数获取的功能-Based on Bayesian theory and learning algorithm for fingerprint identification kits, the use of Bayesian probability theory to achieve fingerprint, signature extraction, characteristics of the func
bayesian1
- 用贝叶斯算法解决数据挖掘中分类问题，先用训练集进行训练，再用测试集进行测试-Bayesian data mining algorithm to solve classification problems in the first training set used for training, re-use test set for testing
bayescode
- 贝叶斯分类，线性非线性分类，神经网络分类-Bayesian classification, linear non-linear classification, neural network classifier
K-meansNB
- ：将K—means算法引入到朴素贝叶斯分类研究中，提出一种基于K—means的朴素贝叶斯分类算法。首先用K— me．arks算法对原始数据集中的完整数据子集进行聚类，计算缺失数据子集中的每条记录与 个簇重心之间的相似度，把记 录赋给距离最近的一个簇，并用该簇相应的属性均值来填充记录的缺失值，然后用朴素贝叶斯分类算法对处理后的数据 集进行分类。实验结果表明，与朴素贝叶斯相比，基于K—means思想的朴素贝叶斯算法具有较高的分类准确率。-: K-means algorithm will
NB
- ：朴素贝叶斯分类器是一种简单而高效的分类器，但是它的属性独立性假设使其无法表示现实世界属性之间的依赖关 系，以及它的被动学习策略，影响了它的分类性能。本文从不同的角度出发，讨论并分析了三种改进朴素贝叶斯分类 性能的方法。为进一步的研究打下坚实的基础。-: Naive Bayesian classifier is a simple and efficient classifier, but its attribute independence assumption that the rea
Bayes_fu
- 用MATLAB实现模式识别中的贝叶斯分类-Using MATLAB to achieve recognition in the Bayesian classifier