The Complete SPRLIB & ANNLIB

weight0_vector

- compute the constant value of the quadratic decision function (LOCAL)

SYNOPSIS

double weight0_vector (Kainv, Kbinv, Ma, Mb, c, n, deta, detb)

ARGUMENTS

double **Kainv The inverse covariance matrix for class A, a matrix of size [1..n][1..n].
double **Kbinv The inverse covariance matrix for class B, a matrix of size [1..n][1..n].
double *Ma The mean vector for class A, a vector of size [1..n].
double *Mb The mean vector for class B, a vector of size [1..n].
double c The quotient of the apriori probabilities.
int n The dimensionality of the feature space.
double deta The determinant of class A.
double detb The determinant of class B.

RETURNS

If no error occured the function returns the constant which is used in the quadratic decision function. In case of an error the function returns -1.0.

FUNCTION

The function determines the constant term used in the quadratic decision function, see fisherq. It receives the necessary inputs for the two classes (inverse covariances, mean and apriori quotient).

NOTE

The variables Ka and Kb are in matrix format, Ma and Mb are in vector format.

SEE ALSO

fisherq

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