Model for classification and regression
Modeler package provides generic tools for learning models
and making predictions in the context of high-throughput data sets
such as those produced by gene expression microarrays. In order to use
this package , you must first prepare a pair of functions (one for
learning models from training data, and one for making predictions on
test data). These functions, along with any required meta-parameters,
are used to create an object of the
object is then passed to the
Modeler function along with
the full training data set.
Kevin R. Coombes firstname.lastname@example.org
The following classification methods have been adapted to use the
Modeler class: K nearest neighbors
learnKNN), recursive partitioning and regression trees
Want to suggest features or report bugs for rdrr.io? Use the GitHub issue tracker.