Update the KNearest classifier using the specific traing data.

Namespace:  Emgu.CV.ML
Assembly:  Emgu.CV.ML (in Emgu.CV.ML.dll) Version: 2.0.0.0 (2.0.0.0)

Syntax

C#
public bool Train(
	Matrix<float> trainData,
	Matrix<float> responses,
	Matrix<byte> sampleIdx,
	bool isRegression,
	int maxK,
	bool updateBase
)
Visual Basic (Declaration)
Public Function Train ( _
	trainData As Matrix(Of Single), _
	responses As Matrix(Of Single), _
	sampleIdx As Matrix(Of Byte), _
	isRegression As Boolean, _
	maxK As Integer, _
	updateBase As Boolean _
) As Boolean
Visual C++
public:
bool Train(
	Matrix<float>^ trainData, 
	Matrix<float>^ responses, 
	Matrix<unsigned char>^ sampleIdx, 
	bool isRegression, 
	int maxK, 
	bool updateBase
)

Parameters

trainData
Type: Emgu.CV..::.Matrix<(Of <(Single>)>)
The training data. A 32-bit floating-point, single-channel matrix, one vector per row
responses
Type: Emgu.CV..::.Matrix<(Of <(Single>)>)
A floating-point matrix of the corresponding output vectors, one vector per row.
sampleIdx
Type: Emgu.CV..::.Matrix<(Of <(Byte>)>)
Can be null if not needed. When specified, identifies samples of interest. It is a Matrix>int< of nx1
isRegression
Type: System..::.Boolean
Specify the output variables type. It can be either categorical (isRegression=false) or ordered (isRegression=true)
maxK
Type: System..::.Int32
The number of maximum neighbors that may be passed to the method findNearest.
updateBase
Type: System..::.Boolean
If true, the existing classifer is updated using the new training data; Otherwise, the classifier is trained from scratch

Return Value

[Missing <returns> documentation for "M:Emgu.CV.ML.KNearest.Train(Emgu.CV.Matrix{System.Single},Emgu.CV.Matrix{System.Single},Emgu.CV.Matrix{System.Byte},System.Boolean,System.Int32,System.Boolean)"]

See Also