The data.mat
needs to suits the base-learner. For instance, the
spline base-learner does just take a one column matrix since there are
just one dimensional splines till now. Additionally, using the polynomial
base-learner the data.mat
is used to control if a intercept should
be fitted or not by adding a column containing just ones. It is also
possible to add other columns to estimate multiple features
simultaneously. Anyway, this is not recommended in terms of unbiased
features selection.
The data.mat
and data.identifier
of a target data object
is set automatically by passing the source and target object to the
desired factory. getData()
can then be used to access the
transformed data of the target object.
This class is a wrapper around the pure C++
implementation. To see
the functionality of the C++
class visit
https://schalkdaniel.github.io/compboost/cpp_man/html/classdata_1_1_in_memory_data.html.