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By combining constant, linear, and quadratic local models, lazy estimates the value of an unknown multivariate function on the basis of a set of possibly noisy samples of the function itself. This implementation of lazy learning automatically adjusts the bandwidth on a query-by-query basis through a leave-one-out cross-validation.
| Version: | 1.2-18 |
| Published: | 2022-10-21 |
| Author: | Mauro Birattari and Gianluca Bontempi |
| Maintainer: | Theo Verhelst <theo.verhelst at ulb.be> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| Copyright: | see file COPYRIGHTS |
| NeedsCompilation: | yes |
| CRAN checks: | lazy results |
| Reference manual: | lazy.pdf |
| Package source: | lazy_1.2-18.tar.gz |
| Windows binaries: | r-devel: lazy_1.2-18.zip, r-release: lazy_1.2-18.zip, r-oldrel: lazy_1.2-18.zip |
| macOS binaries: | r-release (arm64): lazy_1.2-18.tgz, r-oldrel (arm64): lazy_1.2-18.tgz, r-release (x86_64): lazy_1.2-18.tgz, r-oldrel (x86_64): lazy_1.2-18.tgz |
| Old sources: | lazy archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.