代码搜索：Learning
找到约 5,352 项符合「Learning」的源代码
代码结果 5,352
www.eeworm.com/read/474600/6813558
m rbf_network.m
function [test_targets, mu, Wo] = RBF_Network(train_patterns, train_targets, test_patterns, Nh)
% Classify using a backpropagation network with a batch learning algorithm
% Inputs:
% train_patte
www.eeworm.com/read/172122/9723824
m buildgda.m
function dataGDA=BuildGDA(L,S)
% build the GDA data, with L learning vectors, and S an vector of the class sizes.
% L uses line vectors, S is a line vector
% Gaston Baudat & Fatiha Anouar / 21st
www.eeworm.com/read/289487/8548681
m knn.m
function [ypred,tabkppv,distance]=knn(xapp,yapp,valY,X,k)
%
% knn implementation
%
% USE : [ypred,tabkppv,distance]=knn(xapp,yapp,valY,X,k)
%
% xapp, yapp : learning data
% valY : all the Y value pos
www.eeworm.com/read/431675/8662329
m learnlm.m
function j = learnlm(p,d)
%LEARNLM Levenberg-Marquardt learning rule.
%
% LEARNLM(P,D)
% P - RxQ matrix of input (column) vectors.
% D - SxQ matrix of delta (column) vectors.
% Returns:
% Par
www.eeworm.com/read/428269/8880493
m knn.m
function [ypred,tabkppv,distance]=knn(xapp,yapp,valY,X,k)
%
% knn implementation
%
% USE : [ypred,tabkppv,distance]=knn(xapp,yapp,valY,X,k)
%
% xapp, yapp : learning data
% valY : all the Y value pos
www.eeworm.com/read/377948/9256235
m nnd12vl.m
function nnd12vl(cmd,arg1)
%NND12VL Variable learning rate backpropagation demonstration.
%
% This demonstration requires the Neural Network Toolbox.
% First Version, 8-31-95.
%==============
www.eeworm.com/read/361257/10062617
m nnd12vl.m
function nnd12vl(cmd,arg1)
%NND12VL Variable learning rate backpropagation demonstration.
%
% This demonstration requires the Neural Network Toolbox.
% First Version, 8-31-95.
%==============
www.eeworm.com/read/159921/10588467
m perceptr.m
function [alpha,theta,solution,t]=perceptr(X,J,tmax,t,alpha,theta)
% PERCEPTR Perceptron learning rule searching for decision hyperplane.
% [alpha,theta,solution,t]=perceptr(X,J,tmax,t,alpha,theta)
%