代码搜索：Contain
找到约 10,000 项符合「Contain」的源代码
代码结果 10,000
www.eeworm.com/read/486654/6524178
cpp 1592.cpp
/* This Code is Submitted by wywcgs for Problem 1592 on 2006-06-24 at 20:05:56 */
#include
#include
using namespace std;
const int TN = 128;
const char R[][16] = { "NONDI
www.eeworm.com/read/486654/6524185
cpp 1278.cpp
/* This Code is Submitted by wywcgs for Problem 1278 on 2005-11-12 at 15:11:14 */
#include
#include
#include
using namespace std;
const int MAX = 128;
typede
www.eeworm.com/read/486654/6524643
cpp 2243.cpp
/* This Code is Submitted by wywcgs for Problem 2243 on 2006-05-22 at 20:19:40 */
#include
#include
using namespace std;
const int BN = 10;
const int MN = 256;
class M
www.eeworm.com/read/482915/6616178
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/481966/6633477
cpp 1592.cpp
/* This Code is Submitted by wywcgs for Problem 1592 on 2006-06-24 at 20:05:56 */
#include
#include
using namespace std;
const int TN = 128;
const char R[][16] = { "NONDI
www.eeworm.com/read/481966/6633484
cpp 1278.cpp
/* This Code is Submitted by wywcgs for Problem 1278 on 2005-11-12 at 15:11:14 */
#include
#include
#include
using namespace std;
const int MAX = 128;
typede
www.eeworm.com/read/481966/6633942
cpp 2243.cpp
/* This Code is Submitted by wywcgs for Problem 2243 on 2006-05-22 at 20:19:40 */
#include
#include
using namespace std;
const int BN = 10;
const int MN = 256;
class M
www.eeworm.com/read/408407/11389514
txt msi_readme.txt
msi plugin v1.2 for Total Commander
installation:
- unzip the msi.wcx to your Total Commander installation directory
- choose the menu configuration - options
- choose the packer tab
- click
www.eeworm.com/read/408235/11401222
html data-representation.html
CHICKEN User's Manual - Data representation
Data representationNote: In all cases below, bits are numbered sta
www.eeworm.com/read/260625/11716719
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