Update the KNearest classifier using the specific traing data.
| C# | Visual Basic | Visual C++ |
public static bool CvKNearestTrain( IntPtr classifier, IntPtr trainData, IntPtr responses, IntPtr sampleIdx, bool isRegression, int maxK, bool updateBase )
- classifier (IntPtr)
- The KNearest classifier to be updated
- trainData (IntPtr)
- The training data. A 32-bit floating-point, single-channel matrix, one vector per row
- responses (IntPtr)
- A floating-point matrix of the corresponding output vectors, one vector per row.
- sampleIdx (IntPtr)
- Can be IntPtr.Zero if not needed. When specified, identifies samples of interest. It is a Matrix>int< of nx1
- isRegression (Boolean)
- Specify the output variables type. It can be either categorical (isRegression=false) or ordered (isRegression=true)
- maxK (Int32)
- The number of maximum neighbors that may be passed to the method findNearest.
- updateBase (Boolean)
- If true, the existing classifer is updated using the new training data; Otherwise, the classifier is trained from scratch
[Missing <returns> documentation for M:Emgu.CV.ML.MlInvoke.CvKNearestTrain(System.IntPtr,System.IntPtr,System.IntPtr,System.IntPtr,System.Boolean,System.Int32,System.Boolean)]