get_sample_class_knnT_get_sample_class_knnGetSampleClassKnnGetSampleClassKnnget_sample_class_knn (算子名称)

名称

get_sample_class_knnT_get_sample_class_knnGetSampleClassKnnGetSampleClassKnnget_sample_class_knn — Return a training sample from the training data of a K-最近邻 (k-NN) classifier.

参数签名

get_sample_class_knn( : : KNNHandle, IndexSample : 特征, ClassID)

Herror T_get_sample_class_knn(const Htuple KNNHandle, const Htuple IndexSample, Htuple* 特征, Htuple* ClassID)

void GetSampleClassKnn(const HTuple& KNNHandle, const HTuple& IndexSample, HTuple* 特征, HTuple* ClassID)

HTuple HClassKnn::GetSampleClassKnn(Hlong IndexSample, HTuple* ClassID) const

static void HOperatorSet.GetSampleClassKnn(HTuple KNNHandle, HTuple indexSample, out HTuple 特征, out HTuple classID)

HTuple HClassKnn.GetSampleClassKnn(int indexSample, out HTuple classID)

def get_sample_class_knn(knnhandle: HHandle, index_sample: int) -> Tuple[Sequence[float], Sequence[int]]

描述

get_sample_class_knnget_sample_class_knnGetSampleClassKnnGetSampleClassKnnGetSampleClassKnnget_sample_class_knn reads a training sample from the K-最近邻 (k-NN) classifier given by KNNHandleKNNHandleKNNHandleKNNHandleKNNHandleknnhandle that was added with add_sample_class_knnadd_sample_class_knnAddSampleClassKnnAddSampleClassKnnAddSampleClassKnnadd_sample_class_knn or read_class_knnread_class_knnReadClassKnnReadClassKnnReadClassKnnread_class_knn. The index of the sample is specified with IndexSampleIndexSampleIndexSampleIndexSampleindexSampleindex_sample. The index is counted from 0, i.e., IndexSampleIndexSampleIndexSampleIndexSampleindexSampleindex_sample must be a number between 0 and NumSamplesNumSamplesNumSamplesNumSamplesnumSamplesnum_samples - 1, where NumSamplesNumSamplesNumSamplesNumSamplesnumSamplesnum_samples can be determined with get_sample_num_class_knnget_sample_num_class_knnGetSampleNumClassKnnGetSampleNumClassKnnGetSampleNumClassKnnget_sample_num_class_knn. The training sample is returned in 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 a feature vector of length NumDimNumDimNumDimNumDimnumDimnum_dim (see create_class_knncreate_class_knnCreateClassKnnCreateClassKnnCreateClassKnncreate_class_knn), while ClassIDClassIDClassIDClassIDclassIDclass_id is the class label, which is a number between 0 and the number of classes.

运行信息

参数表

KNNHandleKNNHandleKNNHandleKNNHandleKNNHandleknnhandle (input_control)  class_knn HClassKnn, HTupleHHandleHTupleHtuple (handle) (IntPtr) (HHandle) (handle)

Handle of the k-NN classifier.

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

Index of the training sample.

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

Feature vector of the training sample.

ClassIDClassIDClassIDClassIDclassIDclass_id (output_control)  integer-array HTupleSequence[int]HTupleHtuple (integer) (int / long) (Hlong) (Hlong)

Class of the training sample.

结果

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

可能的前置算子

add_sample_class_train_dataadd_sample_class_train_dataAddSampleClassTrainDataAddSampleClassTrainDataAddSampleClassTrainDataadd_sample_class_train_data

参考其它

create_class_knncreate_class_knnCreateClassKnnCreateClassKnnCreateClassKnncreate_class_knn

模块

Foundation