reextractFDAFeatures

(<a rd-options="" href="/link/Task?package=mlr&version=2.17.0" data-mini-rdoc="mlr::Task">Task</a> | <a rd-options="" href="/link/data.frame?package=mlr&version=2.17.0" data-mini-rdoc="mlr::data.frame">data.frame</a>)
Task or data.frame to extract functional features from. Must contain functional features
as matrix columns.

(<code>extractFDAFeatDesc</code>)
FDAFeature extraction description as returned by <a rd-options="" href="/link/extractFDAFeatures?package=mlr&version=2.17.0" data-mini-rdoc="mlr::extractFDAFeatures">extractFDAFeatures</a>

desc

(any)
Further args passed on to methods.

This function accepts a data frame or a task and an extractFDAFeatDesc
(a FDA feature extraction description)
as returned by <a rd-options="" href="/link/extractFDAFeatures?package=mlr&version=2.17.0" data-mini-rdoc="mlr::extractFDAFeatures">extractFDAFeatures</a> to extract features
from previously unseen data.

Interface to a large number of classification and
regression techniques, including machine-readable parameter
descriptions. There is also an experimental extension for survival
analysis, clustering and general, example-specific cost-sensitive
learning. Generic resampling, including cross-validation,
bootstrapping and subsampling. Hyperparameter tuning with modern
optimization techniques, for single- and multi-objective problems.
Filter and wrapper methods for feature selection. Extension of basic
learners with additional operations common in machine learning, also
allowing for easy nested resampling. Most operations can be
parallelized.

Patrick Schratz

Machine Learning in R

Bernd Bischl

Michel Lang

Lars Kotthoff

Julia Schiffner

Jakob Richter

Zachary Jones

Giuseppe Casalicchio

Mason Gallo

Jakob Bossek

Erich Studerus

Leonard Judt

Tobias Kuehn

Pascal Kerschke

Florian Fendt

Philipp Probst

Xudong Sun

Janek Thomas

Bruno Vieira

Laura Beggel

Quay Au

Martin Binder

Florian Pfisterer

Stefan Coors

Steve Bronder

Alexander Engelhardt

Christoph Molnar

Annette Spooner

reextractFDAFeatures function

(<a rd-options='' href='Task'>Task</a> | <a rd-options='' href='data.frame'>data.frame</a>)
Task or data.frame to extract functional features from. Must contain functional features
as matrix columns.

(<code>extractFDAFeatDesc</code>)
FDAFeature extraction description as returned by <a rd-options='' href='extractFDAFeatures'>extractFDAFeatures</a>

This function accepts a data frame or a task and an extractFDAFeatDesc
(a FDA feature extraction description)
as returned by <a rd-options='' href='extractFDAFeatures'>extractFDAFeatures</a> to extract features
from previously unseen data.

Re-extract features from a data set — reextractFDAFeatures

Re-extract features from a data set

reextractFDAFeatures: Re-extract features from a data set

Description

Usage

Arguments

Value