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/330850/12864813
m interactive_learning.m
function test_targets = Interactive_Learning(train_patterns, train_targets, test_patterns, params)
% Classify using nearest neighbors and interactive learning
% Inputs:
% train_patterns - Train
www.eeworm.com/read/137365/13326344
lnt co-arch.lnt
// co-arch.lnt
// Compiler Options for Archimedes C
// This file contains options to allow PC-lint to process source
// files for your compiler. It is used as follows:
//
//
www.eeworm.com/read/317622/13500842
m interactive_learning.m
function test_targets = Interactive_Learning(train_patterns, train_targets, test_patterns, params)
% Classify using nearest neighbors and interactive learning
% Inputs:
% train_patterns - Train
www.eeworm.com/read/316604/13520417
m interactive_learning.m
function D = Interactive_Learning(train_features, train_targets, params, region);
% Classify using nearest neighbors and interactive learning
% Inputs:
% features- Train features
% targets - Tr
www.eeworm.com/read/312163/13617447
m knnrule.m
function model=knnrule(data,K)
% KNNRULE Creates K-nearest neighbours classifier.
%
% Synopsis:
% model=knnrule(data)
% model=knnrule(data,K)
%
% Description:
% It creates model of the K-nearest ne
www.eeworm.com/read/147422/5729643
m w5_ed_ad.m
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% w5_edit_adjust.m
%
% jmw
% 6/20/94
%
% User-Specified Maps: Edit Window
% Callback for "adjust" b
www.eeworm.com/read/135709/5880611
cpp bezier.cpp
/*****************************************************************************
* bezier.cpp
*****************************************************************************
* Copyright (C) 2003 VideoL
www.eeworm.com/read/213911/6312093
m intexa.m
%已知数据
t = 1900:10:1990;
p = [75.995 91.972 105.711 123.203 131.669...
150.697 179.323 203.212 226.505 249.633];
%使用不同的方法进行插值运算
x = 1900:0.01:1990;
yi_linear=interp1(t,p,x);
yi_spli
www.eeworm.com/read/359185/6352509
m interactive_learning.m
function D = Interactive_Learning(train_features, train_targets, params, region);
% Classify using nearest neighbors and interactive learning
% Inputs:
% features- Train features
% targets - Tr
www.eeworm.com/read/493206/6398487
m interactive_learning.m
function D = Interactive_Learning(train_features, train_targets, params, region);
% Classify using nearest neighbors and interactive learning
% Inputs:
% features- Train features
% targets - Tr