Guido Kraemer

That's the R philosophy :-), there is lots of code that does so. Also "dangerous" is a strong word, if you deal with medium size data in R you have...

I missed some techniques, e.g. Autoencoders, Non Negative Matrix Factorization, Local Tangent Space Alignment, SNE and derivates, ... I will implement them when I find some time. Spontaneous idea: for...

first commit for the autoencoder https://github.com/gdkrmr/dimRed/commit/ed647560db2b3dca7e9a89a875ac5a80d3daa5ed

there is a really cool new one: umap: https://github.com/ropenscilabs/umapr https://arxiv.org/abs/1802.03426 currently only a wrapper with reticulate around a python implementation, there is also another package: https://github.com/tkonopka/umap both not on CRAN...

there is also largeVis: LargeVis which already is on cran EDIT: largeVis got archived

Add methods KECA and OKECA.

> Some other possible methods to consider: > > * Sparse PCA > > * [sparsepca](https://cran.r-project.org/web/packages/sparsepca/index.html) > * [nsprcomp](https://cran.r-project.org/web/packages/nsprcomp/nsprcomp.pdf) > > * Robust PCA > > * [FastHCS](https://cran.r-project.org/web/packages/FastHCS/FastHCS.pdf) > >...

- I did the renaming, autoencoders are called nl-PCA in literature related to Meteorology, but autoencoder is probably the better name. - I did a quick search and I am...

It is the first time I hear about this, sounds quite interesting! I gave it a quick read so please correct me if I am doing something wrong. In the...

I think something like ```R embed(data, "DataDepth", classes = cl, ...) ``` where `classes` can either be some vector with classes or a function that returns a vector of classes...