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/255755/12057879

m nmsc.m

%NMSC Nearest Mean Scaled Classifier % % W = NMSC(A) % % INPUT % A Trainign dataset % % OUTPUT % W Nearest Mean Scaled Classifier mapping % % DESCRIPTION % Computation of the linear discrim
www.eeworm.com/read/150905/12248406

m nmc.m

%NMC Nearest Mean Classifier % % W = NMC(A) % % INPUT % A Dataset % % OUTPUT % W Nearest Mean Classifier % % DESCRIPTION % Computation of the nearest mean classifier between the classe
www.eeworm.com/read/150905/12249114

m nmsc.m

%NMSC Nearest Mean Scaled Classifier % % W = NMSC(A) % % INPUT % A Trainign dataset % % OUTPUT % W Nearest Mean Scaled Classifier mapping % % DESCRIPTION % Computation of the linear discrim
www.eeworm.com/read/150495/12289857

html nearestsites.html

JTides Help | Nearest Sites
www.eeworm.com/read/149739/12352764

m nmc.m

%NMC Nearest Mean Classifier % % W = NMC(A) % % INPUT % A Dataset % % OUTPUT % W Nearest Mean Classifier % % DESCRIPTION % Computation of the nearest mean classifier between the classe
www.eeworm.com/read/149739/12353479

m nmsc.m

%NMSC Nearest Mean Scaled Classifier % % W = NMSC(A) % % INPUT % A Trainign dataset % % OUTPUT % W Nearest Mean Scaled Classifier mapping % % DESCRIPTION % Computation of the linear discrim
www.eeworm.com/read/230176/14303036

m quant.m

%QUANT Quantize the input by rounding to the nearest LSB function y = quant(x, lsb) y = lsb * round(x/lsb);
www.eeworm.com/read/127236/14366892

m regroutl.m

function [W] = RegrOutl(X,W) % [W] = RegrOutl(X,W) % [W] = RegrOutl(X) % % Function eliminates outliers interactively. % Feedback is given on the graphical screen - % mouse clicks toggle
www.eeworm.com/read/225910/14511418

m match.m

% num = match(image1, image2) % % This function reads two images, finds their SIFT features, and % displays lines connecting the matched keypoints. A match is accepted % only if its distance is l
www.eeworm.com/read/224369/14595501

m nnclassfn.m

%function [testPerf,rankmat,rank] = nnclassFn(train,test,trainClass,answer) % %Reads in training examples, test examples, class labels of training %examples, and correct class of test examples. Data a