Description Usage Arguments Details Value References See Also Examples
Similarity-based method designed to select the most relevant instances for subsequent classification with a nearest neighbor rule. For more information, see 'Details' and 'References' sections.
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formula |
A formula describing the classification variable and the attributes to be used. |
data, x |
Data frame containing the tranining dataset to be filtered. |
... |
Optional parameters to be passed to other methods. |
classColumn |
positive integer indicating the column which contains the (factor of) classes. By default, the last column is considered. |
RNN
is an extension of CNN
. The latter provides a 'consistent subset', i.e. it is enough
for correctly classifying the rest of instances by means of 1-NN. Then, in the given order, RNN
removes instances
as long as the remaining do not loss the property of being a 'consistent subset'.
Although RNN
is not strictly a class noise filter, it is included here for completeness, since
the origins of noise filters are connected with instance selection algorithms.
An object of class filter
, which is a list with seven components:
cleanData
is a data frame containing the filtered dataset.
remIdx
is a vector of integers indicating the indexes for
removed instances (i.e. their row number with respect to the original data frame).
repIdx
is a vector of integers indicating the indexes for
repaired/relabelled instances (i.e. their row number with respect to the original data frame).
repLab
is a factor containing the new labels for repaired instances.
parameters
is a list containing the argument values.
call
contains the original call to the filter.
extraInf
is a character that includes additional interesting
information not covered by previous items.
Gates G.W. (1972): The Reduced Nearest Neighbour Rule. IEEE Transactions on Information Theory, 18:3 431-433.
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