代码搜索：kernel
找到约 10,000 项符合「kernel」的源代码
代码结果 10,000
www.eeworm.com/read/148788/12426057
m irwls.m
function [nsv,al3,bi,T,Lp]=irwls(x,y,ker,C,par,tol);
%
%
% This function solves the Support Vector Machine for pattern recognition.
%
% [nsv,al3,bi,T,Lp]=irwls(x,y,ker,C,par,tol);
%
% This
www.eeworm.com/read/250172/12426712
h memory.h
/*
* NOTE!!! memcpy(dest,src,n) assumes ds=es=normal data segment. This
* goes for all kernel functions (ds=es=kernel space, fs=local data,
* gs=null), as well as for all well-behaving user prog
www.eeworm.com/read/234502/14110954
m gaussianblur.m
function GI = gaussianBlur(I,s)
% GAUSSIANBLUR blur the image with a gaussian kernel
% GI = gaussianBlur(I,s)
% I is the image, s is the standard deviation of the gaussian
% kernel, a
www.eeworm.com/read/234429/14112910
m contents.m
% ihlf_sv_rfn toolkit
% version 1.0
%
% abaloneexample.m - demonstrate the recusive finite Newton algorithm on Abalone data set
% evalkernel.m - evaluate the kernel function
% ihlf_svr_rfntrain.m
www.eeworm.com/read/131815/14123366
m c_svcdemo.m
% ------- OSU C-SVM CLASSIFIER TOOLBOX Demonstrations---
%
% 1) Construct a linear SVM Classifier and test it
% 2) Construct a nonlinear SVM Classifier (polynomial kernel) and t
www.eeworm.com/read/131815/14123377
m u_svcdemo.m
% ------- OSU nu-SVM CLASSIFIER TOOLBOX Demonstrations---
%
% 1) Construct a linear SVM Classifier and test it
% 2) Construct a nonlinear SVM Classifier (polynomial kernel) and
www.eeworm.com/read/233815/14133862
m dualkmeans.m
function [f,d] = dualkmeans(K,N)
%function [f,d] = dualkmeans(K,N)
%
% Performs dual K-means for ell samples specified by the kernel K
%
%INPUTS
% K = the kernel matrix
% N = the number of cl
www.eeworm.com/read/233815/14133869
m dualpca.m
function [alpha,L,Knew,Ktestnew,Ktestvstest] = dualpca(K,Ktest,k)
%function [alpha,L] = dualpca(K,Ktest,k)
%
% Performs dual PCA
%
%INPUTS
% K = the kernel matrix of the training set (ell x el
www.eeworm.com/read/233815/14133875
m visualise.m
function Tau = visualise(K,k)
%function Tau = visualise(K,k)
%
% Computes a good representation of the data in which cluster
% structure should be visible, and plots the dominant two-
% dimensi
www.eeworm.com/read/131407/14147414
bas vbtrn.bas
Attribute VB_Name = "Readme"
Option Explicit
'需要用的API函数声明:
Declare Function FindWindow Lib "User32" Alias "FindWindowA" (ByVal lpClassName As String, ByVal lpWindowName As String) As Long
Declar