代码搜索：classifier
找到约 4,824 项符合「classifier」的源代码
代码结果 4,824
www.eeworm.com/read/397122/8065904
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/397106/8067630
m svmfwd.m
function [Y, Y1] = svmfwd(net, X)
% SVMFWD - Forward propagation through Support Vector Machine classifier
%
% Y = SVMFWD(NET, X)
% For a data structure NET, the matrix of vectors X is input into
www.eeworm.com/read/397106/8067767
m svm_vccore.m
% Learns classifier and classifies test set
% using the perceptron learning algorithm
% Works with 2 class labels, any number of features
% when the class labels are -1 and 1.
% Invoke using SVM_V
www.eeworm.com/read/397102/8067994
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/397102/8068072
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/397102/8068374
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/331336/12832634
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/139320/13161432
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/326135/13163049
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
www.eeworm.com/read/324303/13273867
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
%