代码搜索：BATCH
找到约 6,125 项符合「BATCH」的源代码
代码结果 6,125
www.eeworm.com/read/162614/5535795
java batchupdateexception.java
/* BatchUpdateException.java -- Exception for batch oriented SQL errors
Copyright (C) 1999, 2000, 2002 Free Software Foundation, Inc.
This file is part of GNU Classpath.
GNU Classpath is free sof
www.eeworm.com/read/162519/5545327
java batchupdateexception.java
/* BatchUpdateException.java -- Exception for batch oriented SQL errors
Copyright (C) 1999, 2000, 2002 Free Software Foundation, Inc.
This file is part of GNU Classpath.
GNU Classpath is free sof
www.eeworm.com/read/474600/6813554
m backpropagation_recurrent.m
function [test_targets, W, J] = Backpropagation_Recurrent(train_patterns, train_targets, test_patterns, params)
% Classify using a backpropagation recurrent network with a batch learning algorithm
www.eeworm.com/read/472930/6859842
h bpn.h
#ifndef _BPN
#define _BPN
#include
enum FuncType{purelin,logsig,tansig};
enum TrainType{adapt, batch};
typedef double REAL;
typedef std::vector RA;
#ifndef NULL
#define NUL
www.eeworm.com/read/193517/8221093
cs batchentry.cs
using System;
using System.Security.Principal;
using System.Diagnostics;
using CSLA;
using CSLA.Resources;
namespace CSLA.BatchQueue.Server
{
///
/// A batch queue entry.
//
www.eeworm.com/read/170936/9779207
m kmeans.m
function [centres, options, post, errlog] = kmeans(centres, data, options)
%KMEANS Trains a k means cluster model.
%
% Description
% CENTRES = KMEANS(CENTRES, DATA, OPTIONS) uses the batch K-means
%
www.eeworm.com/read/367152/9780243
m somke.m
% somke - Batch self-organizing map (k epochs)
%
% function [mamap,mse,majump] = somke(data,npara,snpara,nele,mamap,majump)
%
% INPUTS
% ======
% data : data vectors (col vectors)
% npara : see
www.eeworm.com/read/415313/11076452
m kmeans.m
function [centres, options, post, errlog] = kmeans(centres, data, options)
%KMEANS Trains a k means cluster model.
%
% Description
% CENTRES = KMEANS(CENTRES, DATA, OPTIONS) uses the batch K-means
%
www.eeworm.com/read/415311/11077081
m optimal_brain_surgeon.m
function [D, Wh, Wo] = Optimal_Brain_Surgeon(train_features, train_targets, params, region)
% Classify using a backpropagation network with a batch learning algorithm and remove excess units
% usi
www.eeworm.com/read/413912/11137164
m kmeans.m
function [centres, options, post, errlog] = kmeans(centres, data, options)
%KMEANS Trains a k means cluster model.
%
% Description
% CENTRES = KMEANS(CENTRES, DATA, OPTIONS) uses the batch K-means
%