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nnlib2Rcpp (version 0.1.8)

nnlib2Rcpp-package: A collection of Neural Networks and tools to create custom models

Description

This package contains a collection of ready-to-use Neural Networks (NN), i.e. versions of Autoencoder, Back-Propagation, Learning Vector Quantization and Matrix Associative Memory NN. It also provides a module (NN module) to define and control custom neural networks created from user-defined nnlib2 NN components. More information and examples for each of the above can be found in its help documentation (see below).

Arguments

Ready-to-use Neural Networks:

  • Plain Back-Propagation (BP-supervised) (BP)

  • Learning Vector Quantization (LVQ-supervised) (LVQs)

  • Learning Vector Quantization (LVQ-unsupervised) (LVQu)

  • Matrix Associative Memory (MAM-supervised) (MAM)

  • Autoencoder (unsupervised) (Autoencoder)

Custom Neural Networks:

  • NN module (NN)

References

  • Nikolaidis, V. N., (2021). The nnlib2 library and nnlib2Rcpp R package for implementing neural networks. Journal of Open Source Software, 6(61), 2876, 10.21105/joss.02876.

    References for the ready-to-use NN models (can be found in related help content):

    • Kohonen, T (1988). Self-Organization and Associative Memory, Springer-Verlag.; Simpson, P. K. (1991). Artificial neural systems: Foundations, paradigms, applications, and implementations. New York: Pergamon Press.

    • Pao Y (1989). Adaptive Pattern Recognition and Neural Networks. Reading, MA (US); Addison-Wesley Publishing Co., Inc.

    • Simpson, P. K. (1991). Artificial neural systems: Foundations, paradigms, applications, and implementations. New York: Pergamon Press.

    • Philippidis, TP & Nikolaidis, VN & Kolaxis, JG. (1999). Unsupervised pattern recognition techniques for the prediction of composite failure. Journal of acoustic emission. 17. 69-81.

    • Nikolaidis V.N., Makris I.A, Stavroyiannis S, "ANS-based preprocessing of company performance indicators." Global Business and Economics Review 15.1 (2013): 49-58, 10.1504/GBER.2013.050667.

See Also

More information and examples on using the package can be found in the following vignette:

vignette("manual", package='nnlib2Rcpp')

Related links: