BAYESGAUSS贝叶斯分类器对高斯模式。

D = BAYESGAUSS(X,钙、马、P)计算贝叶斯决策

n维的功能模式的行X。

n-by-n-by-W大小的CA是一个数组,其中包含了协方差

的矩阵大小n-by-n,W类的数量。

大小n-by-W 马是一个数组,其列。柯尔-

水洼意味着向量。一个赔偿。矩阵和平均向量必须

为每个类指定,即使一些都是平等的。X是大小

K-by-n,K是模式的数量分类。P是

1-by-W数组,包含发生的概率

每个类。如果P不包括在参数、类

假定同样可能。-BAYESGAUSS Bayes classifier for Gaussian patterns.

　　D = BAYESGAUSS(X, CA, MA, P) computes the Bayes decision

　　functions of the n-dimensional patterns in the rows of X.

　　CA is an array of size n-by-n-by-W containing W covariance

　　matrices of size n-by-n, where W is the number of classes.

　　MA is an array of size n-by-W, whose columns are the corres-

　　ponding mean vectors. A cov. matrix and a mean vector must be

　　specified for each class, even if some are equal.　X is of size

　　K-by-n, where K is the number of patterns to be classified. P is

　　a 1-by-W array, containing the probabilities of occurrence of

　　each class.　If P is not included in the argument, the classes

　　are assumed to be equally likely.