get_sample_class_knnT_get_sample_class_knnGetSampleClassKnnget_sample_class_knnGetSampleClassKnnGetSampleClassKnn (Operator)

Name

get_sample_class_knnT_get_sample_class_knnGetSampleClassKnnget_sample_class_knnGetSampleClassKnnGetSampleClassKnn — Return a training sample from the training data of a k-nearest neighbors (k-NN) classifier.

Signature

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

Description

get_sample_class_knnget_sample_class_knnGetSampleClassKnnget_sample_class_knnGetSampleClassKnnGetSampleClassKnn reads a training sample from the k-nearest neighbors (k-NN) classifier given by KNNHandleKNNHandleKNNHandleKNNHandleKNNHandleKNNHandle that was added with add_sample_class_knnadd_sample_class_knnAddSampleClassKnnadd_sample_class_knnAddSampleClassKnnAddSampleClassKnn or read_class_knnread_class_knnReadClassKnnread_class_knnReadClassKnnReadClassKnn. The index of the sample is specified with IndexSampleIndexSampleIndexSampleIndexSampleIndexSampleindexSample. The index is counted from 0, i.e., IndexSampleIndexSampleIndexSampleIndexSampleIndexSampleindexSample must be a number between 0 and NumSamples - 1, where NumSamples can be determined with get_sample_num_class_knnget_sample_num_class_knnGetSampleNumClassKnnget_sample_num_class_knnGetSampleNumClassKnnGetSampleNumClassKnn. The training sample is returned in FeaturesFeaturesFeaturesFeaturesFeaturesfeatures and ClassIDClassIDClassIDClassIDClassIDclassID. FeaturesFeaturesFeaturesFeaturesFeaturesfeatures is a feature vector of length NumDim (see create_class_knncreate_class_knnCreateClassKnncreate_class_knnCreateClassKnnCreateClassKnn), while ClassIDClassIDClassIDClassIDClassIDclassID is the class label, which is a number between 0 and the number of classes.

Parallelization

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

Parameters

KNNHandleKNNHandleKNNHandleKNNHandleKNNHandleKNNHandle (input_control) class_knn → (integer)

Handle of the k-NN classifier.

IndexSampleIndexSampleIndexSampleIndexSampleIndexSampleindexSample (input_control) integer → (integer)

Index of the training sample.

FeaturesFeaturesFeaturesFeaturesFeaturesfeatures (output_control) real-array → (real)

Feature vector of the training sample.

ClassIDClassIDClassIDClassIDClassIDclassID (output_control) integer-array → (integer)

Class of the training sample.

Result

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

Possible Predecessors

add_sample_class_train_dataadd_sample_class_train_dataAddSampleClassTrainDataadd_sample_class_train_dataAddSampleClassTrainDataAddSampleClassTrainData

Module

Foundation

Operators