CREATE_NN
CREATE_NN(strNnFileName, bIsPathRelative,
strInputFile, bIsPathRelative, nSkipBefore, nSkipAfter,
strStartLine, strEndLine, bReverseArrays, arrInputColumns,
arrInputColumnNames, arrOutputColumns, arrOutputColumnNames,
nExtractRecords, dStopError, nStopEpoch, nNeuronsLayer1,
nNeuronsLayer2, nNeuronsLayer3, nNeuronsLayer4, nLayers,
nActivation, nAdjustRange, arrOutTabInputColumns,
arrOutTabInputColumnNames, arrOutTabOutputColumns,
arrOutTabOutputColumnNames);
Creates a new NN on disk, parameters are the same as in the
NN dialog tabs.
Parameters:
strNnFileName - name of the network file
bIsPathRelative - is this path absolute, or relative to the
location of the program's executable.
strInputFile - input (lag) file with data
bIsPathRelative - is this path absolute, or relative to the
location of the program's executable.
nSkipBefore - number of lines to skip before the start pattern.
nSkipAfter - number of lines to skip after the start pattern.
strStartLine - start pattern, meaningfull data begin after this line.
Empty string ("") if not used.
strEndLine - the line, at which the data loading should stop.
bReverseArrays - should data arrays be reversed. Make sure this
parameter is correct. For example, if we have already reversed arrays
during the call to CREATE_LAG_FILE, we don't want to reverse
them again.
arrInputColumns - numbers of input columns
arrInputColumnNames - names of input columns
arrOutputColumns - number of output columns
arrOutputColumnNames - names of output columns
nExtractRecords - record extraction method, see
Cortex tutorial for details.
dStopError - error at which to stop learning. 0 if not used.
nStopEpoch - epoch number to stop calculations. 0 if not used.
nNeuronsLayer1 - number of neurons in layer 1
nNeuronsLayer2 - number of neurons in layer 2
nNeuronsLayer3 - number of neurons in layer 3
nNeuronsLayer4 - number of neurons in layer 4
nLayers - number of layers
nActivation - type of the activation function
(0, 1... corresponds to selection in combo box).
nAdjustRange - scaling coefficient
arrOutTabInputColumns - numbers of input columns for "Output" tab
of the dialog.
arrOutTabInputColumnNames - names of input columns for "Output" tab.
arrOutTabOutputColumns - numbers of output columns for "Output" tab
of the dialog.
arrOutTabOutputColumnNames - names of output columns for "Output" tab.
GET_NN_WEIGHTS
array arrWeights = GET_NN_WEIGHTS(hNn, nLayer);
Returns an array, containing weights for all neurons of a given
layer.
Let's say, we are retrieving weights for the 1st layer, and there are
5 neurons in the previous, 0th layer. Then array elements 0 - 4
will contain weights for the 1st neuron, and so on.
GET_NN_DESCRIPTION
array arrDescription = GET_NN_DESCRIPTION(hNn);
Returns an array, containing description of a network.
Array elements:
0 - num of layers
1-4 - num. of neurons in the corresponding layer
5 - Activation type (0 - sigmoid, 1 - tangent)