A platform for advanced Machine Learning research and applications.
The goal of rtemis is to make data science accessible and efficient with no compromise on flexibility.

Online Documentation and vignettes

install.packages("remotes")
remotes::install_github("egenn/rtemis")

Setup and Installation support here

• v. 0.78: First public release, April 2019

• Visualization
  • Static: mplot3 family (base graphics)
  • Dynamic: dplot3 family (plotly)
• Unsupervised Learning
  • Clustering: u.*
  • Decomposition: d.*
• Supervised Learning
  • Classification, Regression, Survival Regression: s.*
• Cross-Decomposition
  • Sparse Canonical Correlation / Sparse Decomposition: x.*
• Meta-Models
  [Have been temporarily removed for updating]
  • Model Stacking: metaMod()
  • Modality Stacking: metaFeat()
  • Group-weighted Stacking: metaGroup()

• Novel algorithms developed in rtemis will generally be added to this public repository as soon as the corresponding papers are published.
• R Documentation is ongoing and should be completed soon.
• rtemis is under active development with many enhancements and extensions in the works

2019 Efstathios D. Gennatas