代码搜索：learner
找到约 833 项符合「learner」的源代码
代码结果 833
www.eeworm.com/read/299717/3851188
m calc_output.m
function [output_data]=calc_output(lrn, in_data)
% [output_data]=learner.calc_output(lrn, in_data)
%
% parameter class
% -----------------------------
% lrn - learner
% in_data - dou
www.eeworm.com/read/13911/286777
m ecoctrain.m
function net = ecoctrain(net, learner1, X, Y, varargin)
% ECOCTRAIN - Train multi class problem with ECOC
%
% NET = ECOCTRAIN(NET, LEARNER, X, Y)
% For an error correcting output code wrapper NET
www.eeworm.com/read/227593/4773957
pm rocchio.pm
package AI::Categorizer::Learner::Rocchio;
$VERSION = '0.01';
use strict;
use Params::Validate qw(:types);
use AI::Categorizer::FeatureVector;
use AI::Categorizer::Learner::Boolean;
use base qw(AI::C
www.eeworm.com/read/325480/3483547
m retrain.m
function lrn = retrain(lrn, dataset)
% lrn=learner.retrain(lrn, dataset)
%
% parameter class
% lrn learner
% dataset data
% G. Raetsch 1.6.98
% Copyright (c) 1998 GMD Berlin - All ri
www.eeworm.com/read/299717/3851178
m retrain.m
function lrn = retrain(lrn, dataset)
% lrn=learner.retrain(lrn, dataset)
%
% parameter class
% lrn learner
% dataset data
% G. Raetsch 1.6.98
% Copyright (c) 1998 GMD Berlin - All ri
www.eeworm.com/read/130196/5963027
m set_c.m
function rn=set_C(rn, C)
% rn=rbf_net_base.get_C(rn, C)
%
% G. Raetsch 1.6.98
% Copyright (c) 1998 GMD Berlin - All rights reserved
% THIS IS UNPUBLISHED PROPRIETARY SOURCE CODE of GMD F
www.eeworm.com/read/325480/3483551
m do_learn.m
function lrn=do_learn(lrn, dataset)
% lrn=learner.do_learn(lrn, dataset)
%
% parameter class
% lrn learner
% dataset data
% G. Raetsch 1.6.98
% Copyright (c) 1998 GMD Berlin - All ri
www.eeworm.com/read/299717/3851182
m do_learn.m
function lrn=do_learn(lrn, dataset)
% lrn=learner.do_learn(lrn, dataset)
%
% parameter class
% lrn learner
% dataset data
% G. Raetsch 1.6.98
% Copyright (c) 1998 GMD Berlin - All ri
www.eeworm.com/read/130196/5963086
m calc_output_steps.m
function [ys, y_nets]=calc_output_steps(bb, XData, steps)
% [ys, y_nets]=adabooster.calc_output_steps(rn, XData, steps)
%
% parameter class
% bb rbf_net_ls
%
www.eeworm.com/read/246586/4492537
entries
/implement-learner-windows.c/1.1.1.1/Wed Jul 9 19:22:47 2003//
/makefile/1.1.1.1/Wed Jul 9 19:22:47 2003//
D/implementlearner////
/implement-learner.c/1.2/Tue Jul 15 20:33:11 2003//