train_halfout_snn.m

来自「神经网络的工具箱, 神经网络的工具箱,」· M 代码 · 共 45 行

function [net, tr_info, dataset] = train_halfout_snn(net, data)
%TRAIN_HALFOUT_SNN Train network on input data, dividing this data at 
%             random in equal sized training and validation sets. 
%             
%  Syntax
%
%   [net, tr_info, dataset] = train_halfout_snn(net, wcf_data)
%
%  Description
%
%   TRAIN_HALFOUT_SNN takes
%     net       - a net_struct with cost function WCF_SNN.
%     wcf_data  - a wcfdata_struct containing the input data set.
%   and returns
%     net       - a net_struct containing a network trained on
%                 training and validation data, which are obtained by
%                 bootstrapping on the input data set.
%     tr_info   - a structure containing information about the
%                 training process.
%     dataset   - a structure with information about the subdivision
%                 of input data in training and validation set.
%
%  See also
%
%    TRAIN_BOOTSTRAP_SNN
%

if strcmp(net.costFcn.name, 'wcf_snn')
   q = size(data.P,2);
   RP = randperm(q);
   ind_LV = RP([1:round(q/2)]);
   ind_VV = RP([round(q/2)+1:q]);
   dataLV = subset_wcfdata_snn(data, ind_LV);
   dataVV = subset_wcfdata_snn(data, ind_VV);
   dataset.trg_ind = ind_LV;
   dataset.val_ind = ind_VV;
   dataset.data  = data;
   [net, tr_info] = train_snn(net, dataLV, dataVV);
else
   errtext = sprintf(...
           'TRAIN_HALFOUT_SNN: Do not know how to subdivide data for %s.', ...
           net.costFcn.name);
   error(errtext);
end