代码给出了高斯分布下的EM算法的设计与实现-Code gives the design and implementation of a Gaussian distribution under the EM algorithm

对于混合高斯分布的情况，使用最大期望算法，通过不断计算每个样本的均值与方差，使得似然函数达到最大值。可以很好地处理满足一定概率分布的数据。 代码中通过mvnrnd()函数，设定其中的参数，产生符合混合高斯分布的一组数据集。-For the case of a mixed Gaussian distribution, using expectation-maximization algorithm, through continuous calculation of the mean and

Just like EM of Gaussian Mixture Model, this is the EM algorithm for fitting Bernoulli Mixture Model. GMM is useful for clustering real value data. However, for binary data (such as bag of word feature) Bernoulli Mixture is more suitable.

Clustering of data points using Gaussian Mixture Model and EM Algorithm