kknn-deprecated: Deprecated Functions in Package kknn
In KlausVigo/kknn: Weighted k-Nearest Neighbors
Description
Usage
Arguments
Value
References
See Also
Description
These functions are provided for compatibility with older versions of R only, and may be defunct as soon as of the next release.
Usage
1
simulation(formula, data, runs = 10, train = TRUE, k = 11, ...)
Arguments
formula
A formula object.
data
Matrix or data frame.
runs
Number of crossvalidation runs.
train
A logical value. If TRUE the training procedure for selecting optimal values of k and kernel is performed.
k
Number or maximal number of neighbors considered, dependent of choice for train.
...
Further arguments passed to or from other methods.
Value
A matrix, containing the mean and variance of the misclassification
error, the absolute and the squared distances.
References
Hechenbichler K. and Schliep K.P. (2004) Weighted k-Nearest-Neighbor Techniques and Ordinal Classification, Discussion Paper 399, SFB 386, Ludwig-Maximilians University Munich
(https://doi.org/10.5282/ubm/epub.1769)
See Also
Defunct and Deprecated
KlausVigo/kknn documentation built on June 4, 2021, 2:42 p.m.
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Description Usage Arguments Value References See Also
Description
These functions are provided for compatibility with older versions of R only, and may be defunct as soon as of the next release.
Usage
1 | simulation(formula, data, runs = 10, train = TRUE, k = 11, ...)
|
Arguments
formula |
A formula object. |
data |
Matrix or data frame. |
runs |
Number of crossvalidation runs. |
train |
A logical value. If TRUE the training procedure for selecting optimal values of k and kernel is performed. |
k |
Number or maximal number of neighbors considered, dependent of choice for train. |
... |
Further arguments passed to or from other methods. |
Value
A matrix, containing the mean and variance of the misclassification error, the absolute and the squared distances.
References
Hechenbichler K. and Schliep K.P. (2004) Weighted k-Nearest-Neighbor Techniques and Ordinal Classification, Discussion Paper 399, SFB 386, Ludwig-Maximilians University Munich (https://doi.org/10.5282/ubm/epub.1769)
See Also
Defunct and Deprecated
R Package Documentation
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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