read_samples_class_mlp🔗
Short description🔗
read_samples_class_mlp — Read the training data of a multilayer perceptron from a file.
Signature🔗
read_samples_class_mlp( class_mlp MLPHandle, filename.read FileName )
Description🔗
read_samples_class_mlp reads training samples from the file
given by FileName and adds them to the training samples
that have already been added to the multilayer perceptron (MLP)
given by MLPHandle. The MLP must be created with
create_class_mlp before calling
read_samples_class_mlp. As described with
train_class_mlp and write_samples_class_mlp, the
operators read_samples_class_mlp,
add_sample_class_mlp, and write_samples_class_mlp
can be used to build up a extensive set of training samples, and
hence to improve the performance of the MLP by retraining the MLP
with extended data sets.
It should be noted that the training samples must have the correct
dimensionality. The feature vectors and target vectors stored in
FileName must have the lengths NumInput and
NumOutput that were specified with
create_class_mlp. If this is not the case an error message
is returned.
Execution information🔗
Execution information
-
Multithreading type: reentrant (runs in parallel with non-exclusive operators).
-
Multithreading scope: global (may be called from any thread).
-
Processed without parallelization.
This operator modifies the state of the following input parameter:
During execution of this operator, access to the value of this parameter must be synchronized if it is used across multiple threads.
Parameters🔗
MLPHandle (input_control, state is modified) class_mlp → (handle)
MLP handle.
FileName (input_control) filename.read → (string)
File name.
Result🔗
If the parameters are valid, the operator
read_samples_class_mlp returns the value 2 (H_MSG_TRUE). If necessary,
an exception is raised.
Combinations with other operators🔗
Combinations
Possible predecessors
Possible successors
Alternatives
See also
Module🔗
Foundation