Train the boost tree using the specific traning data
| C# | Visual Basic | Visual C++ |
public bool Train( Matrix<float> trainData, DATA_LAYOUT_TYPE tflag, Matrix<float> responses, Matrix<int> varIdx, Matrix<int> sampleIdx, Matrix<int> varType, Matrix<int> missingMask, MCvBoostParams param, bool update )
Public Function Train ( _ trainData As Matrix(Of Single), _ tflag As DATA_LAYOUT_TYPE, _ responses As Matrix(Of Single), _ varIdx As Matrix(Of Integer), _ sampleIdx As Matrix(Of Integer), _ varType As Matrix(Of Integer), _ missingMask As Matrix(Of Integer), _ param As MCvBoostParams, _ update As Boolean _ ) As Boolean
- trainData (Matrix<(Of <(Single>)>))
- The training data. A 32-bit floating-point, single-channel matrix, one vector per row
- tflag (DATA_LAYOUT_TYPE)
- data layout type
- responses (Matrix<(Of <(Single>)>))
- A floating-point matrix of the corresponding output vectors, one vector per row.
- varIdx (Matrix<(Of <(Int32>)>))
- Can be null if not needed. When specified, identifies variables (features) of interest. It is a Matrix>int< of nx1
- sampleIdx (Matrix<(Of <(Int32>)>))
- Can be null if not needed. When specified, identifies samples of interest. It is a Matrix>int< of nx1
- missingMask (Matrix<(Of <(Int32>)>))
- Can be null if not needed. When specified, it is an 8-bit matrix of the same size as trainData, is used to mark the missed values (non-zero elements of the mask)
- param (MCvBoostParams)
- The parameters for training the boost tree
- update (Boolean)
- specifies whether the classifier needs to be updated (i.e. the new weak tree classifiers added to the existing ensemble), or the classifier needs to be rebuilt from scratch
[Missing <returns> documentation for M:Emgu.CV.ML.Boost.Train(Emgu.CV.Matrix{System.Single},Emgu.CV.ML.MlEnum.DATA_LAYOUT_TYPE,Emgu.CV.Matrix{System.Single},Emgu.CV.Matrix{System.Int32},Emgu.CV.Matrix{System.Int32},Emgu.CV.Matrix{System.Int32},Emgu.CV.Matrix{System.Int32},Emgu.CV.ML.Structure.MCvBoostParams,System.Boolean)]