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/373460/2761960
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)
%
www.eeworm.com/read/373069/2767165
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)
%
www.eeworm.com/read/369958/2788170
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/366959/2857628
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)
%
www.eeworm.com/read/266483/4272263
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)
%
www.eeworm.com/read/295595/8150931
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/294886/8195702
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/393865/8257883
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/293183/8310840
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/367442/9748197
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)
%