This can be used to implement custom FDA feature extraction.
Takes a learn and a reextract function along with some optional
parameters to those as argument.
makeExtractFDAFeatMethod(learn, reextract, args = list(), par.set = NULL)
Arguments
| learn |
(function(data, target, col, ...))
Function to learn and extract information on functional column col.
Arguments are:
data data.frame
Data.frame containing matricies with one row per observation of a single functional
or time series and one column per meahttps://github.com/mlr-org/mlr/pull/2005/conflict?name=R%252FextractFDAFeatures.R&ancestor_oid=bdc5d882cc86adac456842bebf1a2cf9bb0eb648&base_oid=55d472e23f5c3eb8099607bd9f539034d93e82a4&head_oid=4076800589c60b20acc926e5a545df9f73193b65surement time point.
All entries need to be numeric. target (character(1))
Name of the target variable. Default: “NULL”.
The variable is only set to be consistent with the API. col (character(1) | numeric(1))
column names or indices, the extraction should be performed on.
The function has to return a named list of values. |
| reextract |
(function(data, target, col, ...))
Function used for reextracting data in predict phase.
Can be equal to learn. |
| args |
(list)
Named list of arguments to pass to learn via .... |
| par.set |
(ParamSet)
Paramset added to the learner if used in conjunction with a makeExtractFDAFeatsWrapper.
Can be NULL.` |
See also
