add_sample_class_train_dataT_add_sample_class_train_dataAddSampleClassTrainDataAddSampleClassTrainDataadd_sample_class_train_data (算子名称)
名称
add_sample_class_train_dataT_add_sample_class_train_dataAddSampleClassTrainDataAddSampleClassTrainDataadd_sample_class_train_data — Add a training sample to training data.
参数签名
描述
add_sample_class_train_dataadd_sample_class_train_dataAddSampleClassTrainDataAddSampleClassTrainDataAddSampleClassTrainDataadd_sample_class_train_data adds a training sample to the
training data given by ClassTrainDataHandleClassTrainDataHandleClassTrainDataHandleClassTrainDataHandleclassTrainDataHandleclass_train_data_handle. The
training sample is given by 特征特征特征特征特征特征 and ClassIDClassIDClassIDClassIDclassIDclass_id.
特征特征特征特征特征特征 is the feature vector of the sample, and
consequently must be a real vector of length NumDimNumDimNumDimNumDimnumDimnum_dim, as
specified in create_class_train_datacreate_class_train_dataCreateClassTrainDataCreateClassTrainDataCreateClassTrainDatacreate_class_train_data. ClassIDClassIDClassIDClassIDclassIDclass_id is the
class of the sample. More than one training sample can be added at once.
In this case the parameter OrderOrderOrderOrderorderorder defines in which order
the elements of the feature vectors are passed in 特征特征特征特征特征特征.
If it is set to 'row'"row""row""row""row""row",
the first training sample comes first, the second comes second, and so on.
If it is set to 'column'"column""column""column""column""column", the first dimension of all feature vectors
comes first, and then the second dimension of all feature vectors,
and so on. The third possible mode for OrderOrderOrderOrderorderorder is
'feature_column'"feature_column""feature_column""feature_column""feature_column""feature_column". This mode expects features which were grouped
before with set_feature_lengths_class_train_dataset_feature_lengths_class_train_dataSetFeatureLengthsClassTrainDataSetFeatureLengthsClassTrainDataSetFeatureLengthsClassTrainDataset_feature_lengths_class_train_data
to come completely and row-wise before the second feature, and so on.
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:
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
ClassTrainDataHandleClassTrainDataHandleClassTrainDataHandleClassTrainDataHandleclassTrainDataHandleclass_train_data_handle (input_control, state is modified) class_train_data → HClassTrainData, HTupleHHandleHTupleHtuple (handle) (IntPtr) (HHandle) (handle)
Handle of the training data.
OrderOrderOrderOrderorderorder (input_control) string → HTuplestrHTupleHtuple (string) (string) (HString) (char*)
The order of the feature vector.
Default:
'row'
"row"
"row"
"row"
"row"
"row"
List of values:
'column'"column""column""column""column""column", 'feature_column'"feature_column""feature_column""feature_column""feature_column""feature_column", 'row'"row""row""row""row""row"
特征特征特征特征特征特征 (input_control) number-array → HTupleSequence[float]HTupleHtuple (real) (double) (double) (double)
Feature vector of the training sample.
ClassIDClassIDClassIDClassIDclassIDclass_id (input_control) integer-array → HTupleSequence[int]HTupleHtuple (integer) (int / long) (Hlong) (Hlong)
Class of the training sample.
结果
如果参数均有效，算子
add_sample_class_train_dataadd_sample_class_train_dataAddSampleClassTrainDataAddSampleClassTrainDataAddSampleClassTrainDataadd_sample_class_train_data 返回值 2 (
H_MSG_TRUE)
. If necessary,
an exception is raised.
可能的前置算子
create_class_train_datacreate_class_train_dataCreateClassTrainDataCreateClassTrainDataCreateClassTrainDatacreate_class_train_data
可能的后置算子
add_class_train_data_svmadd_class_train_data_svmAddClassTrainDataSvmAddClassTrainDataSvmAddClassTrainDataSvmadd_class_train_data_svm,
add_class_train_data_knnadd_class_train_data_knnAddClassTrainDataKnnAddClassTrainDataKnnAddClassTrainDataKnnadd_class_train_data_knn,
add_class_train_data_gmmadd_class_train_data_gmmAddClassTrainDataGmmAddClassTrainDataGmmAddClassTrainDataGmmadd_class_train_data_gmm,
add_class_train_data_mlpadd_class_train_data_mlpAddClassTrainDataMlpAddClassTrainDataMlpAddClassTrainDataMlpadd_class_train_data_mlp
参考其它
create_class_train_datacreate_class_train_dataCreateClassTrainDataCreateClassTrainDataCreateClassTrainDatacreate_class_train_data
模块
Foundation