Train the random 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, MCvRTParams param )
- 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 (MCvRTParams)
- The parameters for training the random tree
[Missing <returns> documentation for M:Emgu.CV.ML.RTrees.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.MCvRTParams)]