train_snn.m

来自「神经网络的工具箱, 神经网络的工具箱,」· M 代码 · 共 51 行

function [net, trrecord] = train_snn(net, dataLV, dataVV, dataTV)
%TRAIN_SNN train a feed forward neural network.
%
% Syntax
%
%  [net, tr_info] = train_snn(net_struct, dataLV)
%  [net, tr_info] = train_snn(net_struct, dataLV, dataVV)
%  [net, tr_info] = train_snn(net_struct, dataLV, dataVV, dataTV)
%
% Description
%
%  TRAIN_SNN(net_struct, dataLV, dataVV, dataTV) takes
%    net_struct   - a net_struct_snn containing the neural network
%    dataLV       - the training data set which is passed to
%                   net_struct.costFcn.name
%    dataVV       - the validation data set which is passed to
%                   net_struct.costFcn.name (optional)
%    dataTV       - the test data set which is passed to
%                   net_struct.costFcn.name (optional)
%  and returns
%    net          - a net_struct_snn with the trained network
%    tr_info      - a structure containing information about the
%                   training proces
%
% Example
%
%  MU = 60;
%  data.P = 2*pi*rand(1,MU);
%  data.T = sin(data.P) + 0.1*randn(size(data.P));
%  net = net_struct_snn([1 8 1], {'tansigtf_snn', 'lintf_snn'}, 'trainlm_snn');
%
%  [net, tr_info] = train_snn(net, data)
%   
%
% See also
%
%  NET_STRUCT_SNN
%

%#function traingd_snn traincgp_snn trainlm_snn
if (nargin == 2)
   [net, trrecord] = feval(net.trainFcn.name, net, dataLV); 
elseif (nargin == 3)
   [net, trrecord] = feval(net.trainFcn.name, net, dataLV, dataVV); 
elseif (nargin == 4)
   [net, trrecord] = feval(net.trainFcn.name, net, dataLV, dataVV, dataTV); 
else
   error('TRAIN_SNN: incorrect number of input arguments.');
end