文件名称:fisher
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费希尔线性判别分析代码
Find the Fisher linear separator w (a column vector).
X is is the training set (X is a matrix. Each row of X
is a vector containing the features of a single sample). y is
a column vector with the labels of the training set (1 and -1).
alg is a number between 1 and 3 that specifies how to find w:
alg = 1: w is the generalized eigenvalue of A,B.
alg = 2: w is the solution to Bw = (mu_1-mu_2)
alg = 3: solve the corresponding regression problem- Find the Fisher linear separator w (a column vector).
X is is the training set (X is a matrix. Each row of X
is a vector containing the features of a single sample). y is
a column vector with the labels of the training set (1 and-1).
alg is a number between 1 and 3 that specifies how to find w:
alg = 1: w is the generalized eigenvalue of A,B.
alg = 2: w is the solution to Bw = (mu_1-mu_2)
alg = 3: solve the corresponding regression problem
Find the Fisher linear separator w (a column vector).
X is is the training set (X is a matrix. Each row of X
is a vector containing the features of a single sample). y is
a column vector with the labels of the training set (1 and -1).
alg is a number between 1 and 3 that specifies how to find w:
alg = 1: w is the generalized eigenvalue of A,B.
alg = 2: w is the solution to Bw = (mu_1-mu_2)
alg = 3: solve the corresponding regression problem- Find the Fisher linear separator w (a column vector).
X is is the training set (X is a matrix. Each row of X
is a vector containing the features of a single sample). y is
a column vector with the labels of the training set (1 and-1).
alg is a number between 1 and 3 that specifies how to find w:
alg = 1: w is the generalized eigenvalue of A,B.
alg = 2: w is the solution to Bw = (mu_1-mu_2)
alg = 3: solve the corresponding regression problem
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fisher.m