代码搜索：Learning
找到约 5,352 项符合「Learning」的源代码
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www.eeworm.com/read/299343/3853267
m chap6_4s1.m
%Single Neural Net PID Decouple Controller based on Hebb Learning
%Algorithm to adjust kp,ki,kd
function [sys,x0,str,ts]=exp_pidf(t,x,u,flag)
switch flag,
case 0 % initializations
www.eeworm.com/read/429426/1948874
py c45.py
# Description: Shows how to use C4.5 learner
# Category: learning
# Classes: C45Learner, C45Classifier
# Uses: iris
# Referenced: C45Learner.htm
import orange
#data = orange.E
www.eeworm.com/read/386597/2570232
txt preprocessing.txt
ADDC@Number of partitions:@4@S
AGHC@Number of partitions, Distance:@[4, 'min']@S
BIMSEC@Num of partitions, Nattempts:@[4, 1]@S
Competitive_learning@Number of partitions, eta:@[4, .01]@S
Determinis
www.eeworm.com/read/385191/2594618
svn-base test_sem3.m.svn-base
% learn the structure of "alarm" network. The learning time is so long!
rand('state', 0);
randn('state', 0);
bnet = mk_alarm_bnet;
dag = bnet.dag;
N = length(dag);
ns = bnet.node_sizes;
n
www.eeworm.com/read/385191/2594653
svn-base score_init_cache.m.svn-base
function cache = score_init_cache(N,L)
% SCORE_INIT_CACHE generate an empty cache for local computation in structure learning
% cache = score_init_cache(number_of_nodes,cache_size)
%
% For 2 nodes wit
www.eeworm.com/read/369339/2800870
6 ttt.6
.th TTT VI 11/1/73
.sh NAME
ttt \*- the game of tic-tac-toe
.sh SYNOPSIS
.bd /usr/games/ttt
.sh DESCRIPTION
.it Ttt
is the X and O game popular in the first grade.
This is a learning program that neve
www.eeworm.com/read/475897/6768470
m chap6_4s2.m
%Single Neural Net PID Decouple Controller based on Hebb Learning
%Algorithm to adjust kp,ki,kd
function [sys,x0,str,ts]=exp_pidf(t,x,u,flag)
switch flag,
case 0 % initializations
www.eeworm.com/read/475897/6768474
m chap6_4s1.m
%Single Neural Net PID Decouple Controller based on Hebb Learning
%Algorithm to adjust kp,ki,kd
function [sys,x0,str,ts]=exp_pidf(t,x,u,flag)
switch flag,
case 0 % initializations
www.eeworm.com/read/474600/6813587
txt preprocessing.txt
ADDC@Number of partitions:@4@S
AGHC@Number of partitions, Distance:@[4, 'min']@S
BIMSEC@Num of partitions, Nattempts:@[4, 1]@S
Competitive_learning@Number of partitions, eta:@[4, .01]@S
Determinis