# nnlib2Rcpp: a(nother) R package for Neural Networks

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For anyone interested, **nnlib2Rcpp** is an R package containing a number of Neural Network implementations and is available on GitHub. It can be installed as follows (the usual way for packages on GitHub):

library(devtools) install_github("VNNikolaidis/nnlib2Rcpp")

The NNs are implemented in C++ (using **nnlib2 **C++ class library) and are interfaced with R via **Rcpp** package (which is also required).

The package *currently* includes the following NN implementations:

- A Back-Propagation (BP) multi-layer NN (supervised) for input-output mappings.
- An Autoencoder NN (unsupervised) for dimensionality reduction (a bit like PCA) or dimensionality expansion.
- A Learning Vector Quantization NN (LVQ, supervised) for classification.
- A Self-Organizing Map NN (unsupervised, simplified 1-D variation of SOM) for clustering (a bit like k-means).
- A simple Matrix-Associative-Memory NN (MAM, supervised) for storing input-output vector pairs.

For more information see the package documentation.

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