mlr3spatial: Support for Spatial Objects Within the 'mlr3' Ecosystem
Source:R/zzz.R
mlr3spatial-package.RdExtends the 'mlr3' ML framework with methods for spatial objects. Data storage and prediction are supported for packages 'terra', 'raster' and 'stars'.
Learn mlr3
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
mlr3 extensions
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
Package Options
"mlr3.debug": If set toTRUE, 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 toTRUE, 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.
References
Becker M, Schratz P (2024). mlr3spatial: Support for Spatial Objects Within the 'mlr3' Ecosystem. https://mlr3spatial.mlr-org.com, https://github.com/mlr-org/mlr3spatial.
Author
Maintainer: Marc Becker marcbecker@posteo.de (ORCID)
Authors:
Patrick Schratz patrick.schratz@gmail.com (ORCID)