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/456469/7348876
m learning3.m
clear all;
clc;
format short
format compact
a=zeros(1,10000); %存放冲突，1代表发生冲突，0代表没发生冲突
gamma=0.95; % 折扣因子
state_new=1;
new=zeros(1,20);
m=1;
s=zeros(1,5);
afa=0.1; %learning parame
www.eeworm.com/read/455365/7372862
pdf ensemble learning.pdf
www.eeworm.com/read/454322/7394214
pdf learning python.pdf
www.eeworm.com/read/445921/7588125
pdf learning_flash.pdf
www.eeworm.com/read/436578/7767872
pdf learning_opencv.pdf
www.eeworm.com/read/434746/7802308
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/399996/7816686
m interactive_learning.m
function test_targets = Interactive_Learning(train_patterns, train_targets, test_patterns, params)
% Classify using nearest neighbors and interactive learning
% Inputs:
% train_patterns - Train
www.eeworm.com/read/399996/7817081
m competitive_learning.m
function [patterns, targets, label, W] = Competitive_learning(train_patterns, train_targets, params, plot_on)
% Perform preprocessing using a competitive learning network
% Inputs:
% patterns -
www.eeworm.com/read/299736/7836233
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/397761/8023563
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