代码搜索：classifier
找到约 4,824 项符合「classifier」的源代码
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www.eeworm.com/read/278889/10490719
m deltablssvm.m
function model = deltablssvm(model,a1,a2)
% Bias term correction for the LS-SVM classifier
%
% >> model = deltablssvm(model, b_new)
%
% This function is only useful in the object oriented function
%
www.eeworm.com/read/159921/10587767
m contents.m
% General purpose and others functions for STPRToolbox.
%
% cerror - Calculates classifier error.
% cliplin1 - Clips line according to given window.
% cliplin2 - Clips line starting i
www.eeworm.com/read/159921/10588320
m poaasvm.m
function poaaosvm(model,background)
% POAASVM vizualizes One-Against-All SVM decision rule.
% poaasvm(model,background)
%
% Input:
% model [struct] model of classifier.
% background [int] 0 - no, 1
www.eeworm.com/read/421949/10676254
m deltablssvm.m
function model = deltablssvm(model,a1,a2)
% Bias term correction for the LS-SVM classifier
%
% >> model = deltablssvm(model, b_new)
%
% This function is only useful in the object oriented function
%
www.eeworm.com/read/421949/10676426
m contents.m
% General purpose and others functions for STPRToolbox.
%
% cerror - Calculates classifier error.
% cliplin1 - Clips line according to given window.
% cliplin2 - Clips line starting i
www.eeworm.com/read/421949/10676992
m poaasvm.m
function poaaosvm(model,background)
% POAASVM vizualizes One-Against-All SVM decision rule.
% poaasvm(model,background)
%
% Input:
% model [struct] model of classifier.
% background [int] 0 - no, 1
www.eeworm.com/read/418695/10935189
m perlc.m
%PERLC Linear classifier by linear perceptron
%
% W1 = perlc(A,n,step,w)
%
% Finds the linear discriminant function W1 (a mapping) by n cycles
% of the data through the linear perceptron with ste
www.eeworm.com/read/418695/10935271
m normal_map.m
%NORMAL_MAP Map a dataset on a normal densities based classifier
%
% F = normal_map(A,W)
%
% Maps the dataset A by the normal densities based classfier W on a
% [0,1] interval for each of the clas
www.eeworm.com/read/418695/10935508
m mapping.m
%MAPPING Mapping class constructor
%
% w = mapping(map,d,lablist,k,c,v,par)
%
% A map/classifier object is constructed from:
% d size (any), a set of weights defining the mapping
% lablist size
www.eeworm.com/read/418342/10952584
m bayesgauss.m
function d = bayesgauss(X, CA, MA, P)
%BAYESGAUSS Bayes classifier for Gaussian patterns.
% D = BAYESGAUSS(X, CA, MA, P) computes the Bayes decision
% functions of the n-dimensional patterns in