A Domain Adaptation LEarning Python library.
This package contains implementations of the following methods:
- Transformers (learning feature embeddings):
- Transfer Feature Learning with Joint Distribution Adaptation (JDA) [Long et al., 2013].
- Domain adaptation via transfer component analysis (TCA) [Pan et al., 2009].
- Balanced distribution adaptation (BDA) [Wang et al., 2017].
- Maximum Independence Domain Adaptation (MIDA) [Yan et al., 2017].
- Estimators (learning classifiers):
- Manifold Regularisation Learning Framework (LapSVM, LapRLS) [Belkin et al., 2006].
- Adaptation Regularisation Learning Framework (ARSVM, ARRLS) [Long et al., 2014].
- Side Information Independence Regularised Learning Framework (SIDeRSVM, SIDeRLS) [Zhou et al, 2020].