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/426679/9004401
m nnclassifier.m
% Nearest Neighbour Classifier-NNC
function [NNCrate]=NNclassifier(features,test_features,trnum,tenum,classnum)
% features the matrix that training samples projected on feature subspace(训练样本
www.eeworm.com/read/374411/9407202
m entropygraddist.m
function Dvect=entropyGradDist(npd)
%
% Compute entropy estimate using nearest neighbor estimate
%
% Copyright (C) 2003 Alexander Ihler; distributable under GPL -- see README.txt
pts = getPoi
www.eeworm.com/read/374411/9407208
m entropydist.m
function h=entropyDist(npd)
%
% Compute entropy estimate using nearest neighbor estimate
%
% Copyright (C) 2003 Alexander Ihler; distributable under GPL -- see README.txt
Ce = .57721566490153
www.eeworm.com/read/177674/9442511
m demknn1.m
%DEMKNN1 Demonstrate nearest neighbour classifier.
%
% Description
% The problem consists of data in a two-dimensional space. The data is
% drawn from three spherical Gaussian distributions with prio
www.eeworm.com/read/177129/9468748
m nearestneighborediting.m
function D = NearestNeighborEditing(train_features, train_targets, params, region)
% Classify points using the nearest neighbor editing algorithm
% Inputs:
% train_features - Train features
% t
www.eeworm.com/read/176823/9483197
m demknn1.m
%DEMKNN1 Demonstrate nearest neighbour classifier.
%
% Description
% The problem consists of data in a two-dimensional space. The data is
% drawn from three spherical Gaussian distributions with prio
www.eeworm.com/read/372113/9521086
m nearestneighborediting.m
function [patterns, targets] = NearestNeighborEditing(train_patterns, train_targets, Nmu, plot_on)
%Reduce the number of data points using the nearest neighbor editing algorithm
%Inputs:
% train_
www.eeworm.com/read/167879/9948747
m radnearest.m
function lock=radnearest(y,Y,T,r,p)
%Syntax: lock=radnearest(y,Y,T,r,p)
%__________________________________
%
% Locks the nearest neighbors of a reference point that lie within a
% radius in a ph
www.eeworm.com/read/362008/10023775
m nearestneighborediting.m
function [patterns, targets] = NearestNeighborEditing(train_patterns, train_targets, Nmu, plot_on)
%Reduce the number of data points using the nearest neighbor editing algorithm
%Inputs:
% train_
www.eeworm.com/read/360732/10080608
m hlle.m
function [Y, mse] = HLLE(X,k,d)
%HLLE Runs the standard Hessian LLE implementation of Hessian Eigenmaps
%
% X is the high-dimensional data to be processed
% k is the number of nearest nei