Operator Reference

get_sample_class_train_dataT_get_sample_class_train_dataGetSampleClassTrainDataGetSampleClassTrainDataget_sample_class_train_data (Operator)

get_sample_class_train_dataT_get_sample_class_train_dataGetSampleClassTrainDataGetSampleClassTrainDataget_sample_class_train_data — Return a training sample from training data.

Signature

get_sample_class_train_data( : : ClassTrainDataHandle, IndexSample : Features, ClassID)

Herror T_get_sample_class_train_data(const Htuple ClassTrainDataHandle, const Htuple IndexSample, Htuple* Features, Htuple* ClassID)

void GetSampleClassTrainData(const HTuple& ClassTrainDataHandle, const HTuple& IndexSample, HTuple* Features, HTuple* ClassID)

HTuple HClassTrainData::GetSampleClassTrainData(Hlong IndexSample, Hlong* ClassID) const

static void HOperatorSet.GetSampleClassTrainData(HTuple classTrainDataHandle, HTuple indexSample, out HTuple features, out HTuple classID)

HTuple HClassTrainData.GetSampleClassTrainData(int indexSample, out int classID)

def get_sample_class_train_data(class_train_data_handle: HHandle, index_sample: int) -> Tuple[Sequence[float], int]

Description

get_sample_class_train_dataget_sample_class_train_dataGetSampleClassTrainDataGetSampleClassTrainDataget_sample_class_train_data reads a training sample from the training data given by ClassTrainDataHandleClassTrainDataHandleClassTrainDataHandleclassTrainDataHandleclass_train_data_handle that was added, e.g., with add_sample_class_train_dataadd_sample_class_train_dataAddSampleClassTrainDataAddSampleClassTrainDataadd_sample_class_train_data. The index of the sample is specified with IndexSampleIndexSampleIndexSampleindexSampleindex_sample. The index is counted from 0. That means that IndexSampleIndexSampleIndexSampleindexSampleindex_sample must be a number between 0 and NumSamplesNumSamplesNumSamplesnumSamplesnum_samples - 1, where NumSamplesNumSamplesNumSamplesnumSamplesnum_samples can be determined with get_sample_num_class_train_dataget_sample_num_class_train_dataGetSampleNumClassTrainDataGetSampleNumClassTrainDataget_sample_num_class_train_data. The training sample is returned in FeaturesFeaturesFeaturesfeaturesfeatures and ClassIDClassIDClassIDclassIDclass_id. FeaturesFeaturesFeaturesfeaturesfeatures is a feature vector of length NumDimNumDimNumDimnumDimnum_dim (see create_class_train_datacreate_class_train_dataCreateClassTrainDataCreateClassTrainDatacreate_class_train_data) and ClassIDClassIDClassIDclassIDclass_id is the class of the feature vector.

Execution Information

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

Parameters

ClassTrainDataHandleClassTrainDataHandleClassTrainDataHandleclassTrainDataHandleclass_train_data_handle (input_control)  class_train_data HClassTrainData, HTupleHHandleHTupleHtuple (handle) (IntPtr) (HHandle) (handle)

Handle of training data for a classifier.

IndexSampleIndexSampleIndexSampleindexSampleindex_sample (input_control)  integer HTupleintHTupleHtuple (integer) (int / long) (Hlong) (Hlong)

Number of stored training sample.

FeaturesFeaturesFeaturesfeaturesfeatures (output_control)  real-array HTupleSequence[float]HTupleHtuple (real) (double) (double) (double)

Feature vector of the training sample.

ClassIDClassIDClassIDclassIDclass_id (output_control)  integer HTupleintHTupleHtuple (integer) (int / long) (Hlong) (Hlong)

Class of the training sample.

Result

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

Possible Predecessors

add_sample_class_train_dataadd_sample_class_train_dataAddSampleClassTrainDataAddSampleClassTrainDataadd_sample_class_train_data

See also

create_class_train_datacreate_class_train_dataCreateClassTrainDataCreateClassTrainDatacreate_class_train_data

Module

Foundation