read_samples_class_svmT_read_samples_class_svmReadSamplesClassSvmReadSamplesClassSvmread_samples_class_svm (算子名称)

名称

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

参数签名

描述

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 NumFeaturesNumFeaturesNumFeaturesNumFeaturesnumFeaturesnum_features and NumClassesNumClassesNumClassesNumClassesnumClassesnum_classes 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.

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 read_samples_class_svmread_samples_class_svmReadSamplesClassSvmReadSamplesClassSvmReadSamplesClassSvmread_samples_class_svm 返回值 2 ( H_MSG_TRUE) . If necessary, an exception is raised.

可能的前置算子

create_class_svmcreate_class_svmCreateClassSvmCreateClassSvmCreateClassSvmcreate_class_svm

可能的后置算子

train_class_svmtrain_class_svmTrainClassSvmTrainClassSvmTrainClassSvmtrain_class_svm

可替代算子

add_sample_class_svmadd_sample_class_svmAddSampleClassSvmAddSampleClassSvmAddSampleClassSvmadd_sample_class_svm

参考其它

write_samples_class_svmwrite_samples_class_svmWriteSamplesClassSvmWriteSamplesClassSvmWriteSamplesClassSvmwrite_samples_class_svm, clear_samples_class_svmclear_samples_class_svmClearSamplesClassSvmClearSamplesClassSvmClearSamplesClassSvmclear_samples_class_svm

模块

Foundation

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