read_samples_class_svmT_read_samples_class_svmReadSamplesClassSvmReadSamplesClassSvmread_samples_class_svm (Operator)
Name
read_samples_class_svmT_read_samples_class_svmReadSamplesClassSvmReadSamplesClassSvmread_samples_class_svm — Read the training data of a support vector machine from a file.
Signature
Description
read_samples_class_svmread_samples_class_svmReadSamplesClassSvmReadSamplesClassSvmReadSamplesClassSvmread_samples_class_svm reads training samples from the file
given by FileNameFileNameFileNameFileNamefileNamefile_name and adds them to the training samples
that have already been added to the support vector machine (SVM)
given by SVMHandleSVMHandleSVMHandleSVMHandleSVMHandlesvmhandle. The SVM must be created with
create_class_svmcreate_class_svmCreateClassSvmCreateClassSvmCreateClassSvmcreate_class_svm before calling
read_samples_class_svmread_samples_class_svmReadSamplesClassSvmReadSamplesClassSvmReadSamplesClassSvmread_samples_class_svm. As described with
train_class_svmtrain_class_svmTrainClassSvmTrainClassSvmTrainClassSvmtrain_class_svm and write_samples_class_svmwrite_samples_class_svmWriteSamplesClassSvmWriteSamplesClassSvmWriteSamplesClassSvmwrite_samples_class_svm, the
operators read_samples_class_svmread_samples_class_svmReadSamplesClassSvmReadSamplesClassSvmReadSamplesClassSvmread_samples_class_svm,
add_sample_class_svmadd_sample_class_svmAddSampleClassSvmAddSampleClassSvmAddSampleClassSvmadd_sample_class_svm, and write_samples_class_svmwrite_samples_class_svmWriteSamplesClassSvmWriteSamplesClassSvmWriteSamplesClassSvmwrite_samples_class_svm
can be used to build up a extensive set of training samples, and
hence to improve the performance of the SVM by retraining the SVM
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
FileNameFileNameFileNameFileNamefileNamefile_name must have the lengths NumFeatures and
NumClasses that were specified with
create_class_svmcreate_class_svmCreateClassSvmCreateClassSvmCreateClassSvmcreate_class_svm. The target is stored in vector form for
compatibility reason with the MLP (see
read_samples_class_mlpread_samples_class_mlpReadSamplesClassMlpReadSamplesClassMlpReadSamplesClassMlpread_samples_class_mlp). If the dimensions are incorrect an
error message is returned.
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
SVMHandleSVMHandleSVMHandleSVMHandleSVMHandlesvmhandle (input_control, state is modified) class_svm → HClassSvm, HTupleHHandleHTupleHtuple (handle) (IntPtr) (HHandle) (handle)
SVM handle.
FileNameFileNameFileNameFileNamefileNamefile_name (input_control) filename.read → HTuplestrHTupleHtuple (string) (string) (HString) (char*)
File name.
Result
If the parameters are valid the operator
read_samples_class_svmread_samples_class_svmReadSamplesClassSvmReadSamplesClassSvmReadSamplesClassSvmread_samples_class_svm returns the value 2 (H_MSG_TRUE). If
necessary, an exception is raised.
Possible Predecessors
create_class_svmcreate_class_svmCreateClassSvmCreateClassSvmCreateClassSvmcreate_class_svm
Possible Successors
train_class_svmtrain_class_svmTrainClassSvmTrainClassSvmTrainClassSvmtrain_class_svm
Alternatives
add_sample_class_svmadd_sample_class_svmAddSampleClassSvmAddSampleClassSvmAddSampleClassSvmadd_sample_class_svm
See also
write_samples_class_svmwrite_samples_class_svmWriteSamplesClassSvmWriteSamplesClassSvmWriteSamplesClassSvmwrite_samples_class_svm,
clear_samples_class_svmclear_samples_class_svmClearSamplesClassSvmClearSamplesClassSvmClearSamplesClassSvmclear_samples_class_svm
Module
Foundation