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 DOI: 10.32614/CRAN.package.validann 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 Documentation: Reference manual: validann.pdf Downloads: 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 dependencies: Reverse suggests: NNbenchmark Linking:Please use the canonical form https://CRAN.R-project.org/package=validann to link to this page.
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