For each input vector (which are rows of the matrix samples) the method finds k <= get_max_k() nearest neighbor. In case of regression, the predicted result will be a mean value of the particular vector's neighbor responses. In case of classification the class is determined by voting.
Namespace: Emgu.CV.MLAssembly: Emgu.CV.ML (in Emgu.CV.ML.dll) Version: 2.2.1.1150 (2.2.1.1150)
Syntax
C# | Visual Basic | Visual C++ |
Parameters
- classifier
- IntPtr
The KNearest classifier
- samples
- IntPtr
The sample matrix where each row is a sample
- k
- Int32
The number of nearest neighbor to find
- results
- IntPtr
Can be IntPtr.Zero if not needed. If regression, return a mean value of the particular vector's neighbor responses; If classification, return the class determined by voting.
- kNearestNeighbors
- array<IntPtr>[]()[][]
Should be IntPtr.Zero if not needed. Setting it to non-null values incures a performance panalty. A matrix of (k * samples.Rows) rows and (samples.Cols) columns that will be filled the data of the K nearest-neighbor for each sample
- neighborResponses
- IntPtr
Should be IntPtr.Zero if not needed. The response of the neighbors. A vector of k*_samples->rows elements.
- dist
- IntPtr
Should be IntPtr.Zero if not needed. The distances from the input vectors to the neighbors. A vector of k*_samples->rows elements.