learn_sampset_box — Train the classifier with one data set.
learn_sampset_box trains the classifier with data for the key SampKey (see read_sampset). The training sequence is terminated at least after NSamples examples. If NSamples is bigger than the number of examples in SampKey, then a cyclic start at the beginning occurs. If the error underpasses the value StopError, then the training sequence is prematurely terminated. StopError is calculated with N / ErrorN. Whereby N means the number of examples which were wrong classified during the last ErrorN training examples. Typically ErrorN is the number of examples in SampKey and NSamples is a multiple of it. If you want a data set with 100 examples to run 5 times at most and if you want it to terminate with an error lower than 5%, then the corresponding values are NSamples = 500, ErrorN = 100 and StopError = 0.05. A protocol of the training activity is going to be written in file Outfile.
Handle of the classifier.
Number of the data set to train.
Name of the protocol file.
Default value: 'training_prot'
Number of arrays of attributes to learn.
Default value: 500
Classification error for termination.
Default value: 0.05
Error during the assignment.
Default value: 100
learn_sampset_box returns 2 (H_MSG_TRUE). An exception is raised if key SampKey does not exist or there are problems while opening the file.
test_sampset_box, enquire_class_box, write_class_box, close_class_box, clear_sampset
test_sampset_box, enquire_class_box, learn_class_box, read_sampset