Ignore:
Timestamp:
Feb 29, 2008, 12:58:04 PM (14 years ago)
Author:
Markus Ringnér
Message:

NCC fixed for #75

File:
1 edited

Legend:

Unmodified
Added
Removed
  • trunk/yat/classifier/KNN.h

    r1188 r1189  
    4444
    4545  /**
    46      @brief Nearest Neighbor Classifier
     46     \brief Nearest Neighbor Classifier
    4747     
    4848     A sample is predicted based on the classes of its k nearest
     
    6565  public:
    6666    /**
    67        @brief Default constructor.
     67       \brief Default constructor.
    6868       
    6969       The number of nearest neighbors (k) is set to 3. Distance and
     
    7575
    7676    /**
    77        @brief Constructor using an intialized distance measure.
    78        
    79        The number of nearest neighbors (k) is set to 3. This constructor
    80        should be used if Distance has parameters and the user wants
    81        to specify the parameters by initializing Distance prior to
    82        constructing the KNN.
     77       \brief Constructor using an intialized distance measure.
     78       
     79       The number of nearest neighbors (k) is set to
     80       3. NeighborWeighting is initialized using its default
     81       constructor. This constructor should be used if Distance has
     82       parameters and the user wants to specify the parameters by
     83       initializing Distance prior to constructing the KNN.
    8384    */
    8485    KNN(const Distance&);
     
    108109   
    109110    /**
    110        @brief Make predictions for unweighted test data.
     111       \brief Make predictions for unweighted test data.
    111112       
    112113       Predictions are calculated and returned in \a results.  For
     
    120121
    121122    /**   
    122         @brief Make predictions for weighted test data.
     123        \brief Make predictions for weighted test data.
    123124       
    124125        Predictions are calculated and returned in \a results. For
     
    135136
    136137    /**
    137        @brief Train the KNN using unweighted training data with known
     138       \brief Train the KNN using unweighted training data with known
    138139       targets.
    139140       
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