clear_samples_class_svmT_clear_samples_class_svmClearSamplesClassSvmClearSamplesClassSvmclear_samples_class_svm (算子名称)

名称

clear_samples_class_svmT_clear_samples_class_svmClearSamplesClassSvmClearSamplesClassSvmclear_samples_class_svm — Clear the training data of a support vector machine.

参数签名

描述

clear_samples_class_svmclear_samples_class_svmClearSamplesClassSvmClearSamplesClassSvmClearSamplesClassSvmclear_samples_class_svm clears all training samples that have been added to the support vector machine (SVM) SVMHandleSVMHandleSVMHandleSVMHandleSVMHandlesvmhandle with add_sample_class_svmadd_sample_class_svmAddSampleClassSvmAddSampleClassSvmAddSampleClassSvmadd_sample_class_svm or read_samples_class_svmread_samples_class_svmReadSamplesClassSvmReadSamplesClassSvmReadSamplesClassSvmread_samples_class_svm. clear_samples_class_svmclear_samples_class_svmClearSamplesClassSvmClearSamplesClassSvmClearSamplesClassSvmclear_samples_class_svm should only be used if the SVM is trained in the same process that uses the SVM for classification with classify_class_svmclassify_class_svmClassifyClassSvmClassifyClassSvmClassifyClassSvmclassify_class_svm. In this case, the memory required for the training samples can be freed with clear_samples_class_svmclear_samples_class_svmClearSamplesClassSvmClearSamplesClassSvmClearSamplesClassSvmclear_samples_class_svm, and hence memory can be saved. In the normal usage, in which the SVM is trained offline and written to a file with write_class_svmwrite_class_svmWriteClassSvmWriteClassSvmWriteClassSvmwrite_class_svm, it is typically unnecessary to call clear_samples_class_svmclear_samples_class_svmClearSamplesClassSvmClearSamplesClassSvmClearSamplesClassSvmclear_samples_class_svm because write_class_svmwrite_class_svmWriteClassSvmWriteClassSvmWriteClassSvmwrite_class_svm does not save the training samples, and hence the online process, which reads the SVM with read_class_svmread_class_svmReadClassSvmReadClassSvmReadClassSvmread_class_svm, requires no memory for the training samples.

运行信息

• 多线程类型:可重入(与非独占操作符并行运行)。
• 多线程作用域:全局(可以从任何线程调用)。
• 未经并行化处理。

This operator modifies the state of the following input parameter:

• SVMHandleSVMHandleSVMHandleSVMHandleSVMHandlesvmhandle

During execution of this operator, access to the value of this parameter must be synchronized if it is used across multiple threads.

参数表

结果

If the parameters are valid 该算子 clear_samples_class_svmclear_samples_class_svmClearSamplesClassSvmClearSamplesClassSvmClearSamplesClassSvmclear_samples_class_svm 返回值 2 ( H_MSG_TRUE) . If necessary, an exception is raised.

可能的前置算子

train_class_svmtrain_class_svmTrainClassSvmTrainClassSvmTrainClassSvmtrain_class_svm, write_samples_class_svmwrite_samples_class_svmWriteSamplesClassSvmWriteSamplesClassSvmWriteSamplesClassSvmwrite_samples_class_svm

参考其它

create_class_svmcreate_class_svmCreateClassSvmCreateClassSvmCreateClassSvmcreate_class_svm, clear_class_svmclear_class_svmClearClassSvmClearClassSvmClearClassSvmclear_class_svm, add_sample_class_svmadd_sample_class_svmAddSampleClassSvmAddSampleClassSvmAddSampleClassSvmadd_sample_class_svm, read_samples_class_svmread_samples_class_svmReadSamplesClassSvmReadSamplesClassSvmReadSamplesClassSvmread_samples_class_svm

模块

Foundation