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/381500/9089911
m nearest_point.m
%skyhawk#flyinghawk
%计算最后一个相点的最近相点的位置及最短距离
function [idx,min_d,idx1,min_d1]=nearest_point(m,whlsj,whlsl,P)
%参数说明：
%输入：m - 嵌入维数， whlsj － 待分析数据， whlsl - 待分析的数据个数， P - 平均循环周期
% idx - 最后一个相点的最近相
www.eeworm.com/read/377519/9273604
m nearest_point.m
%skyhawk#flyinghawk
%计算最后一个相点的最近相点的位置及最短距离
function [idx,min_d,idx1,min_d1]=nearest_point(m,whlsj,whlsl,P)
%参数说明：
%输入：m - 嵌入维数， whlsj － 待分析数据， whlsl - 待分析的数据个数， P - 平均循环周期
% idx - 最后一个相点的最近相
www.eeworm.com/read/177129/9468754
m nearest_neighbor.m
function D = Nearest_Neighbor(train_features, train_targets, Knn, region)
% Classify using the Nearest neighbor algorithm
% Inputs:
% features - Train features
% targets - Train targets
% Knn
www.eeworm.com/read/372113/9521093
m nearest_neighbor.m
function test_targets = Nearest_Neighbor(train_patterns, train_targets, test_patterns, Knn)
% Classify using the Nearest neighbor algorithm
% Inputs:
% train_patterns - Train patterns
% train_t
www.eeworm.com/read/362008/10023780
m nearest_neighbor.m
function test_targets = Nearest_Neighbor(train_patterns, train_targets, test_patterns, Knn)
% Classify using the Nearest neighbor algorithm
% Inputs:
% train_patterns - Train patterns
% train_t
www.eeworm.com/read/357874/10199054
m nearest_neighbor.m
function test_targets = Nearest_Neighbor(train_patterns, train_targets, test_patterns, Knn)
% Classify using the Nearest neighbor algorithm
% Inputs:
% train_patterns - Train patterns
% train_t
www.eeworm.com/read/162511/10300602
m4 nearest.m4
`/* Implementation of the NEAREST intrinsic
Copyright 2003 Free Software Foundation, Inc.
Contributed by Richard Henderson .
This file is part of the GNU Fortran 95 runtime libr
www.eeworm.com/read/161509/10400142
m nearest_point.m
%skyhawk#flyinghawk
%计算最后一个相点的最近相点的位置及最短距离
function [idx,min_d,idx1,min_d1]=nearest_point(tau,m,whlsj,whlsl,P)
%参数说明：
%输入：m - 嵌入维数， whlsj － 待分析数据， whlsl - 待分析的数据个数， P - 平均循环周期
% idx - 最后一个相点
www.eeworm.com/read/160583/10517015
png agg_nearest.png
www.eeworm.com/read/349842/10796646
m nearest_neighbor.m
function D = Nearest_Neighbor(train_features, train_targets, Knn, region)
% Classify using the Nearest neighbor algorithm
% Inputs:
% features - Train features
% targets - Train targets
% Knn