代码搜索：evaluate
找到约 3,619 项符合「evaluate」的源代码
代码结果 3,619
www.eeworm.com/read/238296/13897347
cpp temp.cpp
/*************************************************************************/
/* */
/* Evaluatation of rulesets */
/* ------------------------ */
/* */
/****************
www.eeworm.com/read/135779/13899893
m fwd.m
function y = fwd(net,x)
w = repmat(net.w, size(x,1), 1);
y = sum((w.*evaluate(net.kernel,x,net.sv))') - net.bias;
y = y';
www.eeworm.com/read/135754/13902019
m fwd.m
function y = fwd(net,x)
w = repmat(net.w, size(x,1), 1);
y = sum((w.*evaluate(net.kernel,x,net.sv))') - net.bias;
y = y';
www.eeworm.com/read/133541/14036072
c eval.c
#include "genocop.h"
/********************************************************************************/
/* */
/*
www.eeworm.com/read/202224/15389225
m mm1201.m
% nested function example
ratpoly1 = nestexample([1 2],[1 2 3]) % (x + 2)/(x^2 + 2x + 3)
ratpoly2 = nestexample([2 1],[3 2 1]) % (2x +1)/(3x^2 + 2x +1)
x=linspace(-10,10); % independent variabl
www.eeworm.com/read/202224/15389229
m mm2003.m
% mm2003.m
x = [0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1];
y = [-.447 1.978 3.28 6.16 7.08 7.34 7.66 9.56 9.48 9.30 11.2];
n = 2;
p = polyfit(x,y,n);
xi = linspace(0,1,100);
yi = polyval(p,xi);
pp = polyfit(x,
www.eeworm.com/read/202224/15389264
m mm2404.m
% mm2404.m
x = [0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1];
y = [-.447 1.978 3.28 6.16 7.08 7.34 7.66 9.56 9.48 9.30 11.2]; % data
n = 2; % order of fit
p = polyfit(x,y,n) % find polynomial coefficients
xi = lin
www.eeworm.com/read/201477/15407375
cpp poly.cpp
// evaluate a polynomial
#include
template
T PolyEval(T coeff[], int n, const T& x)
{// Evaluate the degree n polynomial with
// coefficients coeff[0:n] at the point x.
www.eeworm.com/read/201477/15407763
cpp horner.cpp
// evaluate a polynomial using Horner's rule
#include
template
T Horner(T coeff[], int n, const T& x)
{// Evaluate the degree n polynomial with
// coefficients coeff[0:
www.eeworm.com/read/201363/15409486
m a10.m
O=imread('Lenna.bmp');
figure(1);imshow(O);
NIND = 40; % Number of individuals
MAXGEN =50; % Maximum no. of generations
PRECI = 8; % Precision of variables
GGAP = 0.9; % Generation gap
% Build