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/431675/8662185
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/386050/8768123
m quadrc.m
%QUADRC Quadratic Discriminant Classifier
%
% W = QUADRC(A,R,S)
%
% INPUT
% A Dataset
% R,S 0
www.eeworm.com/read/429504/8804876
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/428849/8834552
m contents.m
% Quadratic discriminant function and data mapping.
%
% lin2quad - Merges linear rule and quadratic mapping.
% qmap - Quadratic data mapping.
% quadclass - Quadratic classifier.
%
% About: St
www.eeworm.com/read/428849/8834810
m ocr_fun.m
function ocr_fun(data)
% OCR_FUN Calls OCR classifier and displays result.
%
% Synopsis:
% ocr_fun(data)
%
% Description:
% This function classifies images of characters stored as columns
% of th
www.eeworm.com/read/428451/8867321
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/427586/8932184
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/183445/9158758
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/180305/9313015
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/376053/9334406
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 in