read_samples_class_mlpT_read_samples_class_mlpReadSamplesClassMlpReadSamplesClassMlpread_samples_class_mlp (算子)
名称
read_samples_class_mlpT_read_samples_class_mlpReadSamplesClassMlpReadSamplesClassMlpread_samples_class_mlp — 从文件中读取多层感知机的训练数据。
签名
描述
read_samples_class_mlpread_samples_class_mlpReadSamplesClassMlpReadSamplesClassMlpReadSamplesClassMlpread_samples_class_mlp reads training samples from the file
given by FileNameFileNameFileNameFileNamefileNamefile_name and adds them to the training samples
that have already been added to the multilayer perceptron (MLP)
given by MLPHandleMLPHandleMLPHandleMLPHandleMLPHandlemlphandle. The MLP must be created with
create_class_mlpcreate_class_mlpCreateClassMlpCreateClassMlpCreateClassMlpcreate_class_mlp before calling
read_samples_class_mlpread_samples_class_mlpReadSamplesClassMlpReadSamplesClassMlpReadSamplesClassMlpread_samples_class_mlp. As described with
train_class_mlptrain_class_mlpTrainClassMlpTrainClassMlpTrainClassMlptrain_class_mlp and write_samples_class_mlpwrite_samples_class_mlpWriteSamplesClassMlpWriteSamplesClassMlpWriteSamplesClassMlpwrite_samples_class_mlp, the
operators read_samples_class_mlpread_samples_class_mlpReadSamplesClassMlpReadSamplesClassMlpReadSamplesClassMlpread_samples_class_mlp,
add_sample_class_mlpadd_sample_class_mlpAddSampleClassMlpAddSampleClassMlpAddSampleClassMlpadd_sample_class_mlp, and write_samples_class_mlpwrite_samples_class_mlpWriteSamplesClassMlpWriteSamplesClassMlpWriteSamplesClassMlpwrite_samples_class_mlp
can be used to build up a extensive set of training samples, and
hence to improve the performance of the MLP by retraining the MLP
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 NumInputNumInputNumInputNumInputnumInputnum_input and
NumOutputNumOutputNumOutputNumOutputnumOutputnum_output that were specified with
create_class_mlpcreate_class_mlpCreateClassMlpCreateClassMlpCreateClassMlpcreate_class_mlp。If this is not the case an error message
is returned.
执行信息
- 多线程类型:可重入(与非独占算子并行运行)。
- 多线程作用域:全局(可从任何线程调用)。
- 未采用并行化处理。
此算子修改后续输入参数的状态:
在执行此算子时,若该参数值需在多个线程间使用,则必须对其访问进行同步。
参数
MLPHandleMLPHandleMLPHandleMLPHandleMLPHandlemlphandle (输入控制,状态被修改) class_mlp → HClassMlp, HTupleHHandleHTupleHtuple (handle) (IntPtr) (HHandle) (handle)
MLP 句柄。
FileNameFileNameFileNameFileNamefileNamefile_name (输入控制) filename.read → HTuplestrHTupleHtuple (string) (string) (HString) (char*)
File name.
结果
如果参数有效,算子
read_samples_class_mlpread_samples_class_mlpReadSamplesClassMlpReadSamplesClassMlpReadSamplesClassMlpread_samples_class_mlp 返回值 2 ( H_MSG_TRUE )。如有必要,则抛出异常。
可能的前趋
create_class_mlpcreate_class_mlpCreateClassMlpCreateClassMlpCreateClassMlpcreate_class_mlp
可能的后继
train_class_mlptrain_class_mlpTrainClassMlpTrainClassMlpTrainClassMlptrain_class_mlp
替代
add_sample_class_mlpadd_sample_class_mlpAddSampleClassMlpAddSampleClassMlpAddSampleClassMlpadd_sample_class_mlp
另见
write_samples_class_mlpwrite_samples_class_mlpWriteSamplesClassMlpWriteSamplesClassMlpWriteSamplesClassMlpwrite_samples_class_mlp,
clear_samples_class_mlpclear_samples_class_mlpClearSamplesClassMlpClearSamplesClassMlpClearSamplesClassMlpclear_samples_class_mlp
模块
基础