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/347918/3161829
java multiplevalidationsample.java
/*
* ValidationSample.java
*
* Created on 11 november 2002, 22.59
* @author pmarrone
*/
package org.joone.samples.engine.validation;
import org.joone.engine.*;
import org.joone.engine.learning
www.eeworm.com/read/290583/3972213
c server_stats.c
/**
* @file server_stats.c
* @author Chris Green
* @date Fri Jun 13 14:28:50 2003
*
* @brief "policy" learning portion of portscan detector
*
* This keeps a table of
www.eeworm.com/read/289126/3995838
c server_stats.c
/**
* @file server_stats.c
* @author Chris Green
* @date Fri Jun 13 14:28:50 2003
*
* @brief "policy" learning portion of portscan detector
*
* This keeps a table of
www.eeworm.com/read/431231/1908725
java decisiontreealgorithm.java
package ai.decision.algorithm;
import java.util.*;
import ai.decision.gui.*;
import ai.common.*;
/**
* An implementation of a decision tree learning algorithm.
* (See Mitchell, Machine
www.eeworm.com/read/407965/2257000
makefile
#
# $RCSfile: Makefile,v $
# $Revision: 1.8 $
# $Date: 2000/03/29 16:11:42 $
# $Locker: $
# author: Tucker Balch
#
THISDIR = src/EDU/cmu/cs/coral
SUBDIRS = abstractrobot clay cmvision cye learning
www.eeworm.com/read/407965/2257001
makefile
#
# $RCSfile: Makefile,v $
# $Revision: 1.2 $
# $Date: 2000/03/07 20:29:51 $
# $Locker: $
# author: Tucker Balch
#
THISDIR = src/EDU/cmu/cs/coral/learning
SUBDIRS =
JAVAFILES = $(shell echo *.java
www.eeworm.com/read/386597/2570095
m backpropagation_batch.m
function [test_targets, Wh, Wo, J] = Backpropagation_Batch(train_patterns, train_targets, test_patterns, params)
% Classify using a backpropagation network with a batch learning algorithm
% Inputs
www.eeworm.com/read/386597/2570110
m backpropagation_quickprop.m
function [test_targets, Wh, Wo, J] = Backpropagation_Quickprop(train_patterns, train_targets, test_patterns, params)
% Classify using a backpropagation network with a batch learning algorithm and q
www.eeworm.com/read/386597/2570193
m backpropagation_cgd.m
function [test_targets, Wh, Wo, errors] = Backpropagation_CGD(train_patterns, train_targets, test_patterns, params)
% Classify using a backpropagation network with a batch learning algorithm and co
www.eeworm.com/read/386597/2570199
m backpropagation_sm.m
function [test_targets, Wh, Wo, J] = Backpropagation_SM(train_patterns, train_targets, test_patterns, params)
% Classify using a backpropagation network with stochastic learning algorithm with mome