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/173443/9658048
pdf learning perl.pdf
www.eeworm.com/read/173343/9662193
chm html_learning.chm
www.eeworm.com/read/173342/9662196
chm linux_learning.chm
www.eeworm.com/read/415311/11077068
m interactive_learning.m
function D = Interactive_Learning(train_features, train_targets, params, region);
% Classify using nearest neighbors and interactive learning
% Inputs:
% features- Train features
% targets - Tr
www.eeworm.com/read/415311/11077317
m competitive_learning.m
function [features, targets, label, W] = Competitive_learning(train_features, train_targets, params, region, plot_on)
% Perform preprocessing using a competitive learning network
% Inputs:
% fea
www.eeworm.com/read/414835/11100915
pdf learning_flash.pdf
www.eeworm.com/read/411667/11234382
m learning_demo.m
% Make a point move in the 2D plane
% State = (x y xdot ydot). We only observe (x y).
% Generate data from this process, and try to learn the dynamics back.
% X(t+1) = F X(t) + noise(Q)
% Y(t) = H X(
www.eeworm.com/read/265862/11251774
pdf javascript_learning.pdf
www.eeworm.com/read/147186/12579245
m learning_demo.m
% Make a point move in the 2D plane
% State = (x y xdot ydot). We only observe (x y).
% Generate data from this process, and try to learn the dynamics back.
% X(t+1) = F X(t) + noise(Q)
% Y(t) = H X(
www.eeworm.com/read/135779/13900199
m learning_c.m
function d=learning_c(x,c)
%中心的学习
%x为np×ni的输入矩阵。
%c为ni×m的初始中心。
%d为ni×m训练好的中心。
d=even_k(x,c); %对输入进行聚类
tr(1)=sumsqr(d-c);
i=0;
while tr(i+1)~=0
c=d;
d=even_k(x,c);
i=i+1;
tr(i