代码搜索：svcplot
找到约 112 项符合「svcplot」的源代码
代码结果 112
www.eeworm.com/read/367444/9747733
m svcplot.m
function [h] = svcplot(X,Y,ker,alpha,bias,aspect,mag,xaxis,yaxis,input)
%SVCPLOT Support Vector Machine Plotting routine
%
% Usage: svcplot(X,Y,ker,alpha,bias,zoom,xaxis,yaxis,input)
%
% Parameters:
www.eeworm.com/read/148342/12474577
m svcplot.m
function [h] = svcplot(X,Y,ker,alpha,bias,aspect,mag,xaxis,yaxis,input)
%SVCPLOT Support Vector Machine Plotting routine
%
% Usage: svcplot(X,Y,ker,alpha,bias,zoom,xaxis,yaxis,input)
%
% Parameters:
www.eeworm.com/read/146640/12628563
m svcplot.m
function [h] = svcplot(X,Y,ker,alpha,bias,aspect,mag,xaxis,yaxis,input)
%SVCPLOT Support Vector Machine Plotting routine
%
% Usage: svcplot(X,Y,ker,alpha,bias,zoom,xaxis,yaxis,input)
%
% Parameters:
www.eeworm.com/read/455967/7360618
m svcplot1.m
function svcplot1(X,Y,ker,alpha,bias,aspect,mag,xaxis,yaxis,input)
%SVCPLOT Support Vector Machine Plotting routine
%
% Usage: svcplot(X,Y,ker,alpha,bias,zoom,xaxis,yaxis,input)
%
% Parameters: X
www.eeworm.com/read/286592/6282763
m svcplot1.m
function svcplot1(X,Y,ker,alpha,bias,aspect,mag,xaxis,yaxis,input)
%SVCPLOT Support Vector Machine Plotting routine
%
% Usage: svcplot(X,Y,ker,alpha,bias,zoom,xaxis,yaxis,input)
%
% Parameters: X
www.eeworm.com/read/289710/8533828
m mysvm.m
clear;clc;
load('Examples\Classification\iris2v13.mat')
[nsv, alpha, bias] = svc(X,Y,ker,C)
[h] = svcplot(X,Y,ker,alpha,bias)
www.eeworm.com/read/280576/10312923
m exc3.m
X=[-0.4 0;0.5 0.5;0.5 0;0.5 -0.5;0 0.5;0 -0.5;-0.5 0.5;-0.5 -0.5;0.5 0; 0.1 0.4];
N=size(X,1);
X=[X;X+rand(N,2).*0.05;X.*2.5;X.*2.5+rand(N,2).*0.05]
N=size(X,1);
Y=zeros(N./2,1)+1;
Y=[Y;zeros(N
www.eeworm.com/read/157630/11680190
txt 说明.txt
-----------S200502106 北京工业大学 皮蕴哲 2006.4.11--------------]
整理别人的代码（原来的是英文）所得：
kernel.m用于内积矩阵的计算
svcplot.m用于绘图
svm168.m是主程序
testlin.m是采用线形内积函数的支持向量机应用的 文件
testrbf.m是采用RBF内积函数的支持向量机应用 的 文件
每个文件
www.eeworm.com/read/280576/10312928
m exc1.m
load('dataspiral.mat');
global p1;
p1=0.5;
ker='rbf';
[nsv, alpha, bias,Xs,Ys,alphas] = svc(X,Y,ker,0.5);
[h] = svcplot(X,Y,ker,alpha,bias);
Ytr =svcoutput(X,Y,Xt,ker,alpha,bias);
[N,d]=size(
www.eeworm.com/read/181816/9236196
m contents.m
% Support Vector Machine Toolbox
% Version 2.0-Aug-1998
%
% Support Vector Classification
%
% svc - Calculate support vectors for classification
% svcplot - Plot 2 dimensiona