dimRed and coRanking - Unifying Dimensionality Reduction in R
Guido Kraemer, Markus Reichstein, Miguel,D. Mahecha · The R Journal · 2018
Dimensionality reduction" (DR) is a widely used approach to find low dimensional and interpretable representations of data that are natively embedded in high-dimensional spaces.DR can be realized by a plethora of methods with different properties, objectives, and, hence, (dis)advantages.The resulting low-dimensional data embeddings are often difficult to compare with objective criteria.Here, we introduce the dimRed and coRanking packages for the R language.These open source software packages enable users to easily access multiple classical and advanced DR methods using a common interface.The packages also provide quality indicators for the embeddings and easy visualization of high dimensional data.The coRanking package provides the functionality for assessing DR methods in the co-ranking matrix framework.In tandem, these packages allow for uncovering complex structures high dimensional data.Currently 15 DR methods are available in the package, some of which were not previously available to R users.Here, we outline the dimRed and coRanking packages and make the implemented methods understandable to the interested reader.