Geomstats: A Python Package for Riemannian Geometry in Machine Learning.
Nina MiolaneAlice Le BrigantJohan MatheBenjamin HouNicolas GuiguiYann ThanwerdasStefan HeyderOlivier PeltreNiklas KoepHadi ZaatitiHatem HajriYann CabanesThomas GeraldPaul ChauchatChristian ShewmakeBernhard KainzClaire DonnatSusan P. HolmesXavier PennecPublished in: CoRR (2020)
Keyphrases
- machine learning
- information geometry
- geodesic distance
- pattern recognition
- machine learning methods
- open source
- decision trees
- three dimensional
- learning algorithm
- text classification
- data mining
- euclidean metric
- shape analysis
- artificial intelligence
- feature selection
- active learning
- information extraction
- computer vision
- riemannian manifolds
- affine invariant
- manifold learning
- learning tasks
- transfer learning
- knowledge acquisition
- programming language
- text mining
- natural language processing
- learning systems
- reinforcement learning
- inductive logic programming
- case study
- data analysis
- information theory
- open source software
- explanation based learning
- software package
- fisher information
- supervised learning
- support vector machine