


lyngby_nn_cmain - Main functions for classifier neural network
function [V, W, EAcc, Info] = ...
lyngby_nn_cmain(X, T, PropertyName, PropertyValue)
Input: X Neural network input
T Target output
Property:
GenOptim { {Free} | EarlyStop |
HiddenUnitsEarlyStop | Pruning |
Pruning1DRegGridSearch |
Pruning2DRegGridSearch ]
Generalization optimization
Validation [ {SingleBlocked} ]
How to compute the generalization
measure
TrainSet [ {not defined} | <indices> ]
Indices for the training
set. Default is all of X.
ValSet [ {not defined} | <indices> ]
Indices for the validation
set. Only used in connection with
"non-free" generalization
optimization. Default is no
validation set.
HiddenUnits { 3 } Number of hidden units, not
counting the threshold unit
Reg { 0.001 } Regularization parameter
(weight decay)
Seed Seed for the random generator for
the weights Matlab 4.x single seed
generator is used. Default is no
seed.
Info [ {0} | 1 ] Determines whether the
iterations, costfunction value and
gradient should be continouosly be
displayed
Output: V Input weights
W Output weights
EAcc Evolution of error.
Info Information about EAcc. Is dependent on the
setting of 'GenOptim'
Classifier neural network for multiple output, ie. more than
two classes.
See also LYNGBY_NN_EMAIN, LYNGBY_NN_QMAIN, LYNGBY_NN_CTRAIN.