poster
2019-12-14, 20:46
我将具有2 features和2000 rows数据xtrain matrix分类为训练，因此维数为2 ，μ是2元素向量，危是协方差矩阵2x2：
xtrain = 0.3630 1.6632 -0.0098 1.8526 -0.0424 1.6840 -0.1565 2.1187 0.5720 -2.7282 -0.7808 1.1357 0.5212 -0.6858 0.1038 1.4735 ... mu = 0.3486 0.8327
sigma = 1.1163 0.0452 0.0452 1.5669 我正在做类似的事情：
mu = mean(xtrain) sigma = cov(xtrain) % 1/y^2 = (2 pi)^p |\Sigma| exp { (x-\mu)' inv(\Sigma) (x-\mu) } p = mvnpdf (xtrain, mu, sigma); 然后计算：
pdfgauss =... 问题是如何使用xtest matrix测试分类器的结果？
I was reading this and it says: To classify data using Bayesian classifier we already know `Prior(w)` and need to compute `p(x/w)`. When `p` is multidimensioanl Gaussian, we can use Matlab internal function "`mvnpdf`". 示例） mvnpdf(X,Mean,Cov)
X
xtrain = 0.3630 1.6632 -0.0098 1.8526 -0.0424 1.6840 -0.1565 2.1187 0.5720 -2.7282 -0.7808 1.1357 0.5212 -0.6858 0.1038 1.4735 ... mu = 0.3486 0.8327
sigma = 1.1163 0.0452 0.0452 1.5669 我正在做类似的事情：
mu = mean(xtrain) sigma = cov(xtrain) % 1/y^2 = (2 pi)^p |\Sigma| exp { (x-\mu)' inv(\Sigma) (x-\mu) } p = mvnpdf (xtrain, mu, sigma); 然后计算：
pdfgauss =... 问题是如何使用xtest matrix测试分类器的结果？
I was reading this and it says: To classify data using Bayesian classifier we already know `Prior(w)` and need to compute `p(x/w)`. When `p` is multidimensioanl Gaussian, we can use Matlab internal function "`mvnpdf`". 示例） mvnpdf(X,Mean,Cov)
X