Back to Adaptive Vision Library website
You are here: Start » Function Reference » Nearest Neighbors » KNN_Train
KNN_Train
Trains KNN classifier using sample data.
Syntax
C++
C#
void avl::KNN_Train ( const avl::KNNModel& inKNNModel, const atl::Array<atl::Array<float> >& inFeatures, const atl::Array< int >& inClasses, avl::KNNModel& outKNNModel )
Parameters
Name | Type | Default | Description | |
---|---|---|---|---|
inKNNModel | const KNNModel& | Initialized KNN model | ||
inFeatures | const Array<Array<float> >& | Array of features array | ||
inClasses | const Array< int >& | Array of classes corresponding to feature array elements | ||
outKNNModel | KNNModel& | Trained KNN model |
Errors
Error type | Description |
---|---|
DomainError | Using uninitialized classifier in KNN_Train. |
DomainError | Input array inFeatures is empty in KNN_Train. |
DomainError | Input array inClasses is empty in KNN_Train. |
DomainError | Input inFeatures contains array of different sizes in KNN_Train. |
DomainError | The inFeatures size is different than inClasses size in KNN_Train. |
DomainError | Array inClasses contains negative values in KNN_Train. |
DomainError | Array inClasses contains values grater than maximal class value in KNN_Train. |