HClassKnn (Class)

Name

HClassKnn — Represents an instance of a k-NearestNeighbor classifier.

Constructors

`ReadClassKnn`		Read the k-NN classifier from a file.
`CreateClassKnn`		Create a k-nearest neighbors (k-NN) classifier.

Finalizer

This operator is not available as a class member but will be called automatically when the resources of the object instances are to be released. This occurs in the finalization stage of garbage collection, or upon an explicit call of the Dispose() method.

ClearClassKnn Clear a k-NN classifier.

Methods

`AddClassTrainDataKnn`		Add training data to a k-nearest neighbors (k-NN) classifier.
`AddSampleClassKnn`		Add a sample to a k-nearest neighbors (k-NN) classifier.
`AddSamplesImageClassKnn`		Add training samples from an image to the training data of a k-Nearest-Neighbor classifier.
`ClassifyClassKnn`		Search for the next neighbors for a given feature vector.
`ClassifyImageClassKnn`		Classify an image with a k-Nearest-Neighbor classifier.
`CreateClassKnn`		Create a k-nearest neighbors (k-NN) classifier.
`CreateClassLutKnn`		Create a look-up table using a k-nearest neighbors classifier (k-NN) to classify byte images.
`DeserializeClassKnn`		Deserialize a serialized k-NN classifier.
`GetClassTrainDataKnn`		Get the training data of a k-nearest neighbors (k-NN) classifier.
`GetParamsClassKnn`		Get parameters of a k-NN classification.
`GetSampleClassKnn`		Return a training sample from the training data of a k-nearest neighbors (k-NN) classifier.
`GetSampleNumClassKnn`		Return the number of training samples stored in the training data of a k-nearest neighbors (k-NN) classifier.
`ReadClassKnn`		Read the k-NN classifier from a file.
`SelectFeatureSetKnn`		Selects an optimal subset from a set of features to solve a certain classification problem.
`SerializeClassKnn`		Serialize a k-NN classifier.
`SetParamsClassKnn`		Set parameters for k-NN classification.
`TrainClassKnn`		Creates the search trees for a k-NN classifier.
`WriteClassKnn`		Save the k-NN classifier in a file.