k-Nearest Neighbour Classification Cross-Validation
k-nearest neighbour classification cross-validation from training set.
matrix or data frame of training set cases.
factor of true classifications of training set
number of neighbours considered.
if this is true, the proportion of the votes for the winning class
are returned as attribute
nearest neighbor search algorithm.
This uses leave-one-out cross validation.
For each row of the training set
(in Euclidean distance) other training set vectors are found, and the classification
is decided by majority vote, with ties broken at random. If there are ties for the
kth nearest vector, all candidates are included in the vote.
factor of classifications of training set.
doubt will be returned as
distances and indice of k nearest neighbors are also returned as attributes.
Shengqiao Li. To report any bugs or suggestions please email: firstname.lastname@example.org.
Ripley, B. D. (1996) Pattern Recognition and Neural Networks. Cambridge.
Venables, W. N. and Ripley, B. D. (2002) Modern Applied Statistics with S. Fourth edition. Springer.
knn.cv in class.
1 2 3 4 5
Want to suggest features or report bugs for rdrr.io? Use the GitHub issue tracker.