mlr3spatial-package | R Documentation |
Extends the 'mlr3' ML framework with methods for spatial objects. Data storage and prediction are supported for packages 'terra', 'raster' and 'stars'.
Book on mlr3: https://mlr3book.mlr-org.com
Use cases and examples gallery: https://mlr3gallery.mlr-org.com
Cheat Sheets: https://github.com/mlr-org/mlr3cheatsheets
Preprocessing and machine learning pipelines: mlr3pipelines
Analysis of benchmark experiments: mlr3benchmark
More classification and regression tasks: mlr3data
Solid selection of good classification and regression learners: mlr3learners
Even more learners: https://github.com/mlr-org/mlr3extralearners
Tuning of hyperparameters: mlr3tuning
Hyperband tuner: mlr3hyperband
Visualizations for many mlr3 objects: mlr3viz
Survival analysis and probabilistic regression: mlr3proba
Cluster analysis: mlr3cluster
Feature selection filters: mlr3filters
Feature selection wrappers: mlr3fselect
Interface to real (out-of-memory) data bases: mlr3db
Performance measures as plain functions: mlr3measures
"mlr3.debug"
: If set to TRUE
, parallelization via future is
disabled to simplify debugging and provide more concise tracebacks. Note that
results computed with debug mode enabled use a different seeding mechanism
and are not reproducible.
"mlr3.allow_utf8_names"
: If set to TRUE
, checks on the feature names
are relaxed, allowing non-ascii characters in column names. This is an
experimental and temporal option to pave the way for text analysis, and will
likely be removed in a future version of the package. analysis.
Maintainer: Marc Becker marcbecker@posteo.de (ORCID)
Authors:
Patrick Schratz patrick.schratz@gmail.com (ORCID)
Becker M, Schratz P (2024). mlr3spatial: Support for Spatial Objects Within the 'mlr3' Ecosystem. R package version 0.6.0, https://mlr3spatial.mlr-org.com.
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