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/135008/5890672
dfm batch_insert.dfm
object frm_Batch_Insert: Tfrm_Batch_Insert
Left = 272
Top = 244
Width = 338
Height = 193
BorderIcons = [biSystemMenu]
Caption = #12304#21830#21697#24555#36895#24405#20837#12305
Co
www.eeworm.com/read/135008/5890752
pas batch_insert.pas
unit Batch_Insert;
interface
uses
Windows, Messages, SysUtils, Variants, Classes, Graphics, Controls, Forms,
Dialogs, ExtCtrls, XPMenu, Grids, StdCtrls, Buttons, ComCtrls;
type
Tfrm_
www.eeworm.com/read/132414/5916704
jsp batch_list.jsp
function includeInvalid(str)
{
if (str.indexOf("'") == -1)
return false
else
return true;
}
fun
www.eeworm.com/read/132414/5917449
jsp batch_list.jsp
function includeInvalid(str)
{
if (str.indexOf("'") == -1)
return false
else
return true;
}
fun
www.eeworm.com/read/130105/5964762
sh batch2.sh
#! /bin/sh
# this script is used in EiC's binary distribution
# It sets up all eic scripts so that #!/dir/eic points
# to eic
usage='
echo ""
echo " usage: batch2.sh
www.eeworm.com/read/359185/6352479
m backpropagation_batch.m
function [D, Wh, Wo] = Backpropagation_Batch(train_features, train_targets, params, region)
% Classify using a backpropagation network with a batch learning algorithm
% Inputs:
% features- Train
www.eeworm.com/read/359185/6352504
m perceptron_batch.m
function D = Perceptron_Batch(train_features, train_targets, params, region)
% Classify using the batch Perceptron algorithm
% Inputs:
% features - Train features
% targets - Train targets
www.eeworm.com/read/493833/6391410
m batch1.m
make_rp;
rp.T = 2.9; rp.name = 'run11'; run_qrd_lsl(rp);
rp.T = 3.1; rp.name = 'run12'; run_qrd_lsl(rp);
rp.T = 3.3; rp.name = 'run13'; run_qrd_lsl(rp);
rp.T = 3.5; rp.name = 'run14'; run_qrd_lsl(rp)
www.eeworm.com/read/493833/6391414
m batch2.m
make_rp;
rp.T = 2.9; rp.name = 'run11'; run_qrd_lsl(rp);
rp.T = 3.1; rp.name = 'run12'; run_qrd_lsl(rp);
rp.T = 3.3; rp.name = 'run13'; run_qrd_lsl(rp);
rp.T = 3.5; rp.name = 'run14'; run_qrd_lsl(rp)
www.eeworm.com/read/493206/6398457
m backpropagation_batch.m
function [D, Wh, Wo] = Backpropagation_Batch(train_features, train_targets, params, region)
% Classify using a backpropagation network with a batch learning algorithm
% Inputs:
% features- Train