mergeBenchmarkResultLearner

[<code><a rd-options="" href="/link/BenchmarkResult?package=mlr&version=2.9" data-mini-rdoc="mlr::BenchmarkResult">BenchmarkResult</a></code>] 
<code>BenchmarkResult</code> objects that should be merged.


Combines the <code><a rd-options="" href="/link/BenchmarkResult?package=mlr&version=2.9" data-mini-rdoc="mlr::BenchmarkResult">BenchmarkResult</a></code> objects that were performed 
  with different learners on the same set of Task(s). 
  This can be helpful if you, e.g. forgot to run one learner on the set of tasks you used.


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.

Bernd Bischl

Machine Learning in R

mergeBenchmarkResultLearner function

[<code><a rd-options='' href='BenchmarkResult'>BenchmarkResult</a></code>] 
<code>BenchmarkResult</code> objects that should be merged.


Combines the <code><a rd-options='' href='BenchmarkResult'>BenchmarkResult</a></code> objects that were performed 
  with different learners on the same set of Task(s). 
  This can be helpful if you, e.g. forgot to run one learner on the set of tasks you used.


mergeBenchmarkResultLearner: Merge different learners of BenchmarkResult objects.

Description

Usage

Arguments