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Methods and tools for analysing and validating the outputs and modelled functions of artificial neural networks (ANNs) in terms of predictive, replicative and structural validity. Also provides a method for fitting feed-forward ANNs with a single hidden layer.
| Version: | 1.2.1 |
| Depends: | R (≥ 3.1.0) |
| Imports: | moments |
| Suggests: | nnet, knitr, rmarkdown |
| Published: | 2017-04-20 |
| Author: | Greer B. Humphrey [aut, cre] |
| Maintainer: | Greer B. Humphrey <greer.humphrey at student.adelaide.edu.au> |
| BugReports: | http://github.com/gbhumphrey1/validann/issues |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: | http://github.com/gbhumphrey1/validann |
| NeedsCompilation: | no |
| Citation: | validann citation info |
| CRAN checks: | validann results |
| Reference manual: | validann.pdf |
| Package source: | validann_1.2.1.tar.gz |
| Windows binaries: | r-devel: validann_1.2.1.zip, r-release: validann_1.2.1.zip, r-oldrel: validann_1.2.1.zip |
| macOS binaries: | r-release (arm64): validann_1.2.1.tgz, r-oldrel (arm64): validann_1.2.1.tgz, r-release (x86_64): validann_1.2.1.tgz, r-oldrel (x86_64): validann_1.2.1.tgz |
| Old sources: | validann archive |
| Reverse suggests: | NNbenchmark |
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