Description Usage Arguments Value Examples
This function implements a probabilistic algorithm
1 2 | ipfProbabilistic(train_fgp, train_pos, group_cols = NULL, groups = NULL,
k = 3, FUN = sum, delta = 1, ...)
|
train_fgp |
a data frame containing the fingerprint vectors of the training set |
train_pos |
a data frame containing the positions of the training set observations |
group_cols |
a character vector with the names of the columns to be used as the criteria to group the fingerprints. By default the groups will be created using all the columns available in the train_pos data frame. |
groups |
a numeric vector of length = nrow(train) containing the group index for the training vectors |
k |
the k parameter for the algorithm (number of similar neighbors) |
FUN |
function to compute the similarity measurement. Default is 'sum' |
delta |
parameter delta |
... |
additional parameters for provided function FUN |
An S3 object of class ipfModel, with the following properties: params -> a list with the parameters passed to the function data -> a list with the fingerprints probabilistic parameters (means and standard deviations) and its locations
1 2 3 4 5 6 7 |
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