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/428849/8834646
m knnclass.m
function y = knnclass(X,model)
% KNNCLASS k-Nearest Neighbours classifier.
%
% Synopsis:
% y = knnclass(X,model)
%
% Description:
% The input feature vectors X are classified using the K-NN
% rule
www.eeworm.com/read/428269/8880521
m svmclassnpa.m
function [xsup,alpha,b,pos]=svmclassnpa(x,y,C,kernel,kerneloption,verbose);
% USAGE
% [xsup,alpha,b,pos]=svmclassnpa(x,y,C,kernel,kerneloption,verbose);
%
%
% Main ROUTINE For Nearest P
www.eeworm.com/read/373632/9445402
r knn.var.r
### Name: knn.var
### Title: K-Nearest Neighbor Classification With Variable Selection
### Aliases: knn.var
### Keywords: models
### ** Examples
data(iris)
set.seed (3)
samp
www.eeworm.com/read/366530/9809903
m dpf_nn_sensor_select.m
% purpose: particle filter for sensor network
%% sensor selection rule : the nearest node by sensor leader be the next
%% sensor leader
% date 2005-11-12
clear all;
clc;
clf;
area=100;%area i
www.eeworm.com/read/362246/10010122
m knnclass.m
function y = knnclass(X,model)
% KNNCLASS k-Nearest Neighbours classifier.
%
% Synopsis:
% y = knnclass(X,model)
%
% Description:
% The input feature vectors X are classified using the K-NN
% rule
www.eeworm.com/read/281020/10272156
m snn.m
% SNN - Creates forecasts of a time series on t+1 using multivariate nearest neighbor algorithm.
%
% REQUIRES MREGRESS.M FILE available at http://www.mathworks.com/matlabcentral/fileexchange/l
www.eeworm.com/read/280595/10311902
m knnclass.m
function y = knnclass(X,model)
% KNNCLASS k-Nearest Neighbours classifier.
%
% Synopsis:
% y = knnclass(X,model)
%
% Description:
% The input feature vectors X are classified using the K-NN
% rule
www.eeworm.com/read/278099/10571840
c dblround.c
/* +++Date last modified: 05-Jul-1997 */
/*
** DBLROUND.C - Rounds a double to the nearest whole number
** public domain by Ross Cottrell
*/
#include
#include
#includ
www.eeworm.com/read/159921/10587730
m~ knnclass.m~
function [class] = knnclass(tst,X,I,K)
% [class] = knnclass(tst,X,I,K)
%
% KNNCLASS is an implementation of K-Nearest Neighbours
% classifier. The Euclidean distance is used.
%
% Input:
% tst [DxNt
www.eeworm.com/read/159920/10589521
c dblround.c
/*
** DBLROUND.C - Rounds a double to the nearest whole number
** public domain by Ross Cottrell
*/
#include
#include
#include
double round(double x)
{