代码搜索：Classify
找到约 2,639 项符合「Classify」的源代码
代码结果 2,639
www.eeworm.com/read/386597/2570212
m rbf_network.m
function [test_targets, mu, Wo] = RBF_Network(train_patterns, train_targets, test_patterns, Nh)
% Classify using a radial basis function network algorithm
% Inputs:
% train_patterns - Train patt
www.eeworm.com/read/386597/2570214
m rce.m
function test_targets = RCE(train_patterns, train_targets, test_patterns, lambda_m)
% Classify using the reduced coulomb energy algorithm
% Inputs:
% train_patterns - Train patterns
% train_tar
www.eeworm.com/read/474600/6813560
m rce.m
function test_targets = RCE(train_patterns, train_targets, test_patterns, lambda_m)
% Classify using the reduced coulomb energy algorithm
% Inputs:
% train_patterns - Train patterns
% train_tar
www.eeworm.com/read/413912/11137523
result dataexample2.txt.result
Processing Filename: demo\DataExample2.txt
Classifier:MCWithMultiFSet -Voting -Separator 1,120,121,150,154,225 -- IIS_classify -Iter 50
Message: Train-Test Split, Boundary: 100, Classification,
Err
www.eeworm.com/read/204769/15333763
cpp initialize.cpp
#include
#include
#include
#include
#include "initialize.h"
//#include "classify.h"
FeaturePtr **example;
FeaturePtr **sv;
double *lambda;
int *s
www.eeworm.com/read/286662/8751756
m nddf.m
function [test_targets, g0, g1] = NDDF(train_patterns, train_targets, test_patterns, cost)
% Classify using the normal density discriminant function
% Inputs:
% train_patterns - Train patterns
www.eeworm.com/read/373627/9445955
html predict.qda.html
R: Classify from Quadratic Discriminant Analysis
www.eeworm.com/read/372113/9521146
m nddf.m
function [test_targets, g0, g1] = NDDF(train_patterns, train_targets, test_patterns, cost)
% Classify using the normal density discriminant function
% Inputs:
% train_patterns - Train patterns
www.eeworm.com/read/362008/10023842
m nddf.m
function [test_targets, g0, g1] = NDDF(train_patterns, train_targets, test_patterns, cost)
% Classify using the normal density discriminant function
% Inputs:
% train_patterns - Train patterns
www.eeworm.com/read/357874/10199089
m nddf.m
function [test_targets, g0, g1] = NDDF(train_patterns, train_targets, test_patterns, cost)
% Classify using the normal density discriminant function
% Inputs:
% train_patterns - Train patterns