

   kk--NNeeaarreesstt NNeeiigghhbboouurr CCllaassssiiffiiccaattiioonn

        knn(train, test, class, k=1, l=1, prob=F, use.all=T)

   AArrgguummeennttss::

      train: matrix or data frame of training set cases.

       test: matrix or data frame of test set cases. A vector
             will be interpreted as a row vector for a single
             case.

      class: factor of true classifications of training set

          k: number of neighbours considered.

          l: minimum vote for definite decision, otherwise
             `doubt'. (More precisely, less than `k-l' dissent-
             ing votes are allowed, even if `k' is increased by
             ties.)

       prob: If this is true, the proportion of the votes for
             the winning class are returned as attribute
             `prob'.

    use.all: controls handling of ties. If true, all distances
             equal to the `k'th largest are included. If false,
             a random selection of distances equal to the `k'th
             is chosen to use exactly `k' neighbours.

   VVaalluuee::

        factor of classifications of test set. `doubt' will be
        returned as `NA'.

   SSeeee AAllssoo::

        `knn1', `knn.cv'

