Changeset 178


Ignore:
Timestamp:
Oct 1, 2004, 11:24:13 AM (18 years ago)
Author:
Jari Häkkinen
Message:

Fixed minor documentation issues and performed spell checking.

Location:
trunk/src
Files:
3 edited

Legend:

Unmodified
Added
Removed
  • trunk/src/NNI.h

    r177 r178  
    3333  /// corrections, whereas a 0 means that the data should be replaced
    3434  /// by an imputed value. Naturally, the weight matrix can also be
    35   /// continuos where values between 0 and 1 defines how certain a
     35  /// continuous where values between 0 and 1 defines how certain a
    3636  /// data element is.
    3737  ///
     
    4242  /// Implementation issues
    4343  ///
    44   /// The current implementation treats rows where all data are tagget
    45   /// are completely uncertatin, i.e. all weights are zero, by
     44  /// The current implementation treats rows where all data are tagged
     45  /// are completely uncertain, i.e. all weights are zero, by
    4646  /// ignoring these lines in nearest neighbourhood
    4747  /// calculations. Importantly, this type of data are not changed
     
    5454  /// number. Identical rows in this context are basically a
    5555  /// comparison between elements with non-zero uncertainty weights
    56   /// only, and all these elemnts are equal. Zero weight elemenets are
     56  /// only, and all these elements are equal. Zero weight elements are
    5757  /// not used in the comparison since these are considered as
    5858  /// non/sense values.
     
    6161  {
    6262  public:
     63
     64    ///
    6365    /// Base constructor for the nearest neighbour imputation
    6466    /// algorithms.
     67    ///
    6568    NNI(const gslapi::matrix& matrix,const gslapi::matrix& weight,
    6669        const u_int neighbours);
     
    6871    virtual ~NNI(void) {};
    6972
     73    ///
    7074    /// @return A const reference to the modified data.
     75    ///
    7176    const gslapi::matrix& imputed_data(void) const { return imputed_data_; }
    7277
  • trunk/src/WeNNI.h

    r177 r178  
    1616
    1717  ///
    18   /// WeNNI is a continous weights generalization of the (binary
    19   /// weights) kNNI algorithm presented by Troyanska et al. A
     18  /// WeNNI is a continuous weights generalization of the (binary
     19  /// weights) kNNI algorithm presented by Troyanskaya et al. A
    2020  /// reference to this paper is found in the NNI document referred to
    2121  /// in the NNI class documentation. The NNI document also describes
     
    2727  {
    2828  public:
    29     /// Perform WeNNI on data in \a matrix with continious uncertainty
     29    /// Perform WeNNI on data in \a matrix with continuous uncertainty
    3030    /// weights in \a weight using \a neighbours for the new impute
    3131    /// value.
  • trunk/src/kNNI.h

    r177 r178  
    1414  ///
    1515  /// kNNI is the binary weight implementation of NNI. This follows
    16   /// the work done by Troyanska et al. cited in the NNI document
     16  /// the work done by Troyanskaya et al. cited in the NNI document
    1717  /// referred to in the NNI class documentation.
    1818  ///
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