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read_samples_class_svmReadSamplesClassSvmReadSamplesClassSvmread_samples_class_svmT_read_samples_class_svm🔗

Short description🔗

read_samples_class_svmReadSamplesClassSvmReadSamplesClassSvmread_samples_class_svmT_read_samples_class_svm — Read the training data of a support vector machine from a file.

Signature🔗

read_samples_class_svm( class_svm SVMHandle, filename.read FileName )void ReadSamplesClassSvm( const HTuple& SVMHandle, const HTuple& FileName )static void HOperatorSet.ReadSamplesClassSvm( HTuple SVMHandle, HTuple fileName )def read_samples_class_svm( svmhandle: HHandle, file_name: str ) -> None

Herror T_read_samples_class_svm( const Htuple SVMHandle, const Htuple FileName )

void HClassSvm::ReadSamplesClassSvm( const HString& FileName ) const

void HClassSvm::ReadSamplesClassSvm( const char* FileName ) const

void HClassSvm::ReadSamplesClassSvm( const wchar_t* FileName ) const (Windows only)

void HClassSvm.ReadSamplesClassSvm( string fileName )

Description🔗

read_samples_class_svmReadSamplesClassSvm reads training samples from the file given by FileNamefileNamefile_name and adds them to the training samples that have already been added to the support vector machine (SVM) given by SVMHandleSVMHandlesvmhandle. The SVM must be created with create_class_svmCreateClassSvm before calling read_samples_class_svmReadSamplesClassSvm. As described with train_class_svmTrainClassSvm and write_samples_class_svmWriteSamplesClassSvm, the operators read_samples_class_svmReadSamplesClassSvm, add_sample_class_svmAddSampleClassSvm, and write_samples_class_svmWriteSamplesClassSvm 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 FileNamefileNamefile_name must have the lengths NumFeaturesnumFeaturesnum_features and NumClassesnumClassesnum_classes that were specified with create_class_svmCreateClassSvm. The target is stored in vector form for compatibility reason with the MLP (see read_samples_class_mlpReadSamplesClassMlp). If the dimensions are incorrect 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🔗

SVMHandleSVMHandlesvmhandle (input_control, state is modified) class_svm → (handle)HTuple (HHandle)HClassSvm, HTuple (IntPtr)HHandleHtuple (handle)

SVM handle.

FileNamefileNamefile_name (input_control) filename.read → (string)HTuple (HString)HTuple (string)strHtuple (char*)

File name.

Result🔗

If the parameters are valid the operator read_samples_class_svmReadSamplesClassSvm returns the value 2 (H_MSG_TRUE). If necessary, an exception is raised.

Combinations with other operators🔗

Combinations

Possible predecessors

create_class_svmCreateClassSvm

Possible successors

train_class_svmTrainClassSvm

Alternatives

add_sample_class_svmAddSampleClassSvm

See also

write_samples_class_svmWriteSamplesClassSvm, clear_samples_class_svmClearSamplesClassSvm

Module🔗

Foundation