get_sample_class_svmT_get_sample_class_svmGetSampleClassSvmget_sample_class_svmGetSampleClassSvmGetSampleClassSvm (Operator)

Name

get_sample_class_svmT_get_sample_class_svmGetSampleClassSvmget_sample_class_svmGetSampleClassSvmGetSampleClassSvm — Return a training sample from the training data of a support vector machine.

Signature

Description

get_sample_class_svmget_sample_class_svmGetSampleClassSvmget_sample_class_svmGetSampleClassSvmGetSampleClassSvm reads out a training sample from the support vector machine (SVM) given by SVMHandleSVMHandleSVMHandleSVMHandleSVMHandleSVMHandle that was added with add_sample_class_svmadd_sample_class_svmAddSampleClassSvmadd_sample_class_svmAddSampleClassSvmAddSampleClassSvm or read_samples_class_svmread_samples_class_svmReadSamplesClassSvmread_samples_class_svmReadSamplesClassSvmReadSamplesClassSvm. The index of the sample is specified with IndexSampleIndexSampleIndexSampleIndexSampleIndexSampleindexSample. The index is counted from 0, i.e., IndexSampleIndexSampleIndexSampleIndexSampleIndexSampleindexSample must be a number between 0 and IndexSamples - 1, where IndexSamples can be determined with get_sample_num_class_svmget_sample_num_class_svmGetSampleNumClassSvmget_sample_num_class_svmGetSampleNumClassSvmGetSampleNumClassSvm. The training sample is returned in FeaturesFeaturesFeaturesFeaturesFeaturesfeatures and TargetTargetTargetTargetTargettarget. FeaturesFeaturesFeaturesFeaturesFeaturesfeatures is a feature vector of length NumFeatures (see create_class_svmcreate_class_svmCreateClassSvmcreate_class_svmCreateClassSvmCreateClassSvm), while TargetTargetTargetTargetTargettarget is the index of the class, ranging between 0 and NumClasses-1 (see add_sample_class_svmadd_sample_class_svmAddSampleClassSvmadd_sample_class_svmAddSampleClassSvmAddSampleClassSvm).

get_sample_class_svmget_sample_class_svmGetSampleClassSvmget_sample_class_svmGetSampleClassSvmGetSampleClassSvm can, for example, be used to reclassify the training data with classify_class_svmclassify_class_svmClassifyClassSvmclassify_class_svmClassifyClassSvmClassifyClassSvm in order to determine which training samples, if any, are classified incorrectly.

Parallelization

• Multithreading type: reentrant (runs in parallel with non-exclusive operators).
• Multithreading scope: global (may be called from any thread).
• Processed without parallelization.

Parameters

Example (HDevelop)

* Train an SVM
create_class_svm (NumFeatures, 'rbf', 0.01, 0.01, NumClasses,\
                  'one-versus-all', 'normalization', NumFeatures,\
                  SVMHandle)
read_samples_class_svm (SVMHandle, 'samples.mtf')
train_class_svm (SVMHandle, 0.001, 'default')
* Reclassify the training samples
get_sample_num_class_svm (SVMHandle, NumSamples)
for I := 0 to NumSamples-1 by 1
    get_sample_class_svm (SVMHandle, I, Data, Target)
    classify_class_svm (SVMHandle, Data, 1, Class)
    if (Class != Target)
        * Sample has been classified incorrectly
    endif
endfor
clear_class_svm (SVMHandle)

Result

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

Possible Predecessors

add_sample_class_svmadd_sample_class_svmAddSampleClassSvmadd_sample_class_svmAddSampleClassSvmAddSampleClassSvm, read_samples_class_svmread_samples_class_svmReadSamplesClassSvmread_samples_class_svmReadSamplesClassSvmReadSamplesClassSvm, get_sample_num_class_svmget_sample_num_class_svmGetSampleNumClassSvmget_sample_num_class_svmGetSampleNumClassSvmGetSampleNumClassSvm, get_support_vector_class_svmget_support_vector_class_svmGetSupportVectorClassSvmget_support_vector_class_svmGetSupportVectorClassSvmGetSupportVectorClassSvm

Possible Successors

classify_class_svmclassify_class_svmClassifyClassSvmclassify_class_svmClassifyClassSvmClassifyClassSvm

See also

create_class_svmcreate_class_svmCreateClassSvmcreate_class_svmCreateClassSvmCreateClassSvm

Module

Foundation