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贝叶斯分类器，模式识别，贝叶斯规则用于C个类，高斯函数建模-Bayesian classifier, pattern recognition, Bayesian rules for C-class, the Gaussian function modeling
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一个强大的统计模式识别工具箱，包含高斯分类器，高斯混合模型，主成分分析，支持向量机等常见分类方法。-A powerful statistical pattern recognition toolbox, including the Gaussian classifier, Gaussian mixture model, principal component analysis, support vector machines and other common classification met
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本贝叶斯分类器可以实现对二维高斯分布样本的分类-The Bayesian classifier can achieve two-dimensional Gaussian distribution of the classification of samples
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模式识别某次课程的作业，完成了高斯分布下的两种贝叶斯分类器,以及非参数的K近邻、Parzen窗方法，采用UCI机器学习数据库中的某些数据作为样本，使用交叉验证方法确定参数-Pattern recognition of a particular course work, completed under the two Gaussian Bayesian classifier, and the non-parametric K-nearest neighbor, Parzen window meth
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2类分类高斯模型
每个类是由一个单一的多元高斯分布的3-D建模
显示如何估计高斯均值向量和协方差矩阵的最大似然（ML）估计的基础上为每个类。
meanA和meanB代表每个类的均值，varA和varB的的代表每个类的协方差矩阵.-2-class classifier with Gaussian Models
Each class is modelled by a single 3-D multivariate Gaussian distribution
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一个小demo,用softmax实现数据分类，数据有4类，均服从高斯分布-A small demo, a classifier with softmax softmax is implemented to classify 4 classes of datas which are generated by gaussian distribution
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一个小demo,用softmax实现数据分类，数据有4类，均服从高斯分布-A little demo, a classifier with softmax softmax is implemented to classify 4 classes of datas which are generated by gaussian distribution
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