代码搜索：TestData
找到约 755 项符合「TestData」的源代码
代码结果 755
www.eeworm.com/read/401180/11563142
m svmlfwd.m
function Y = svmlfwd(net, X, Y)
% SVMLFWD - Wrapper for SVMlight: Prediction
%
% YPRED = SVMLFWD(NET, X)
% Predict labels YPRED for points X using the SVMlight stored in NET.
% Each row of X
www.eeworm.com/read/173141/5378396
properties importexport_app.properties
supportfiles=testData/ImportExport/EndOfFile.txt
usedefaults=true
useextdirs=true
www.eeworm.com/read/169190/5426534
in runtest.in
#! /bin/sh
# This file is generated by configure from RunTest.in. Make any changes
# to that file.
# Run PCRE tests
cf=diff
testdata=@top_srcdir@/testdata
# Select which tests to run; if no select
www.eeworm.com/read/169190/5426536
runtest
#! /bin/sh
# Run PCRE tests
cf=diff
# Select which tests to run; if no selection, run all
do1=no
do2=no
do3=no
do4=no
while [ $# -gt 0 ] ; do
case $1 in
1) do1=yes;;
2) do2=yes;;
3)
www.eeworm.com/read/393565/8275363
m svmlfwd.m
function Y = svmlfwd(net, X, Y)
% SVMLFWD - Wrapper for SVMlight: Prediction
%
% YPRED = SVMLFWD(NET, X)
% Predict labels YPRED for points X using the SVMlight stored in NET.
% Each row of X
www.eeworm.com/read/415313/11076967
m svmlfwd.m
function Y = svmlfwd(net, X, Y)
% SVMLFWD - Wrapper for SVMlight: Prediction
%
% YPRED = SVMLFWD(NET, X)
% Predict labels YPRED for points X using the SVMlight stored in NET.
% Each row of X
www.eeworm.com/read/413912/11137597
m svmlfwd.m
function Y = svmlfwd(net, X, Y)
% SVMLFWD - Wrapper for SVMlight: Prediction
%
% YPRED = SVMLFWD(NET, X)
% Predict labels YPRED for points X using the SVMlight stored in NET.
% Each row of X
www.eeworm.com/read/248950/12534085
m svmlfwd.m
function Y = svmlfwd(net, X, Y)
% SVMLFWD - Wrapper for SVMlight: Prediction
%
% YPRED = SVMLFWD(NET, X)
% Predict labels YPRED for points X using the SVMlight stored in NET.
% Each row of X
www.eeworm.com/read/430149/8763942
c ch08_13.c
#include
union memory
{
int a;
char b;
int c[4];
};
int main(void)
{
union memory testData;
printf("size of testData :%d\n", sizeof(testData));
printf(
www.eeworm.com/read/182157/9214677
m knn.m
function TestClasses=knn(k,GlassData,GlassClasses,TestData)
GlassData0=averageM(GlassData);
TestData0=averageM(TestData);
[rowTest,colTest]=size(TestData0);
TestClasses=zeros(rowTest,1);
for ii=1