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/398324/7994268
m train.m
function net = train(net, tutor, varargin)
% TRAIN
%
% Train a max-win multi-class support vector classifier network using the
% specified tutor to train each component two-class network.
%
www.eeworm.com/read/398324/7994447
m train.m
function net = train(net, tutor, varargin)
% TRAIN
%
% Train a max-win multi-class support vector classifier network using the
% specified tutor to train each component two-class network.
%
www.eeworm.com/read/398324/7994604
m train.m
function net = train(net, tutor, varargin)
% TRAIN
%
% Train a max-win multi-class support vector classifier network using the
% specified tutor to train each component two-class network.
%
www.eeworm.com/read/397106/8067613
m local_polynomial_vc.m
% Learns classifier and classifies test set
% using local polynomial approximations of the density
% Usage
% [train_error, test_error] = Local_Polynomial_VC(train_features, train_labels,Nlp ,test
www.eeworm.com/read/397102/8067972
m medianc.m
%MEDIANC Median combining classifier
%
% W = medianc(V)
% W = V*medianc
%
% If V = [V1,V2,V3, ... ] is a set of classifiers trained on the
% same classes and W is the median combiner: it selects
www.eeworm.com/read/397102/8068034
m prodc.m
%PRODC Product combining classifier
%
% W = prodc(V)
% W = V*prodc
%
% If V = [V1,V2,V3, ... ] is a set of classifiers trained on the
% same classes and W is the product combiner: it selects the
www.eeworm.com/read/245176/12813189
m train.m
function net = train(net, tutor, varargin)
% TRAIN
%
% Train a max-win multi-class support vector classifier network using the
% specified tutor to train each component two-class network.
%
www.eeworm.com/read/245176/12813321
m train.m
function net = train(net, tutor, varargin)
% TRAIN
%
% Train a max-win multi-class support vector classifier network using the
% specified tutor to train each component two-class network.
%
www.eeworm.com/read/245176/12813330
m train.m
function net = train(net, tutor, varargin)
% TRAIN
%
% Train a dag-svm multi-class support vector classifier network using the
% specified tutor to train each component two-class network.
%
www.eeworm.com/read/143706/12849463
m test_classify.m
function run = test_classify(classifier)
warning('off','MATLAB:colon:operandsNotRealScalar');
% clear global preprocess;
global preprocess;
global temp_train_file temp_test_file temp_output_f