代码搜索：Nearest
找到约 1,596 项符合「Nearest」的源代码
代码结果 1,596
www.eeworm.com/read/187479/8636710
cc trenne.cc
// auswertung der Ausgaben der range- und nearest-narbor-query
#include
#include
int main(int a, char **argv)
{
char infilename[30];
char outfilename[30];
FILE *in, *out[10]
www.eeworm.com/read/386050/8767491
m testk.m
%TESTK Error estimation of the K-NN rule
%
% E = TESTK(A,K,T)
%
% INPUT
% A Training dataset
% K Number of nearest neighbors (default 1)
% T Test dataset (default [], i.e. find leave-one-out e
www.eeworm.com/read/179030/9377957
ini oeminfo.ini
[Version]
Microsoft Windows Whistler Edition
WinVer=5.01
[Support Information]
Line1="Please mail or fax to the nearest ASUS technical support."
Line2=""
Line3="ASUSTeK COMPUTER INC. (Asia-Pac
www.eeworm.com/read/373632/9445442
html knn.var.html
R: K-Nearest Neighbor Classification With Variable Selection
www.eeworm.com/read/299984/7140008
m testk.m
%TESTK Error estimation of the K-NN rule
%
% E = TESTK(A,K,T)
%
% INPUT
% A Training dataset
% K Number of nearest neighbors (default 1)
% T Test dataset (default [], i.e. find leave-one-out e
www.eeworm.com/read/460435/7250483
m testk.m
%TESTK Error estimation of the K-NN rule
%
% E = TESTK(A,K,T)
%
% INPUT
% A Training dataset
% K Number of nearest neighbors (default 1)
% T Test dataset (default [], i.e. find leave-one-out e
www.eeworm.com/read/450608/7480125
m testk.m
%TESTK Error estimation of the K-NN rule
%
% E = TESTK(A,K,T)
%
% INPUT
% A Training dataset
% K Number of nearest neighbors (default 1)
% T Test dataset (default [], i.e. find leave-one-out e
www.eeworm.com/read/442927/7641782
m srchbbt1nn.m
function [NNINDEX, NNDIST, DISTCOMPCOUNT] = srchbbt1nn(vec, tree, alldata)
% SRCHBBT1NN Branch-and-bound tree search for 1 nearest neighbor.
% Usage: [NNINDEX, NNDIST, DISTCOMPCOUNT] = srchbbt1nn(ve
www.eeworm.com/read/441245/7672689
m testk.m
%TESTK Error estimation of the K-NN rule
%
% E = TESTK(A,K,T)
%
% INPUT
% A Training dataset
% K Number of nearest neighbors (default 1)
% T Test dataset (default [], i.e. find leave-one-out e
www.eeworm.com/read/137160/13341893
m testk.m
%TESTK Error estimation of the K-NN rule
%
% E = TESTK(A,K,T)
%
% INPUT
% A Training dataset
% K Number of nearest neighbors (default 1)
% T Test dataset (default [], i.e. find leave-one-out e