ADAPT is an open-source python library providing the implementation of several domain adaptation methods. The library is suited for scikit-learn estimator object (object which implement fit and predict methods) and tensorflow models. Most of the implemented methods are developed in an estimator agnostic fashion, offering various possibilities adapted to multiple usage. The library offers three modules corresponding to the three principal strategies of domain adaptation: (i) feature-based containing methods performing feature transformation; (ii) instance-based with the implementation of reweighting techniques and (iii) parameter-based proposing methods to adapt pre-trained models to novel observations. A full documentation is proposed online https://adapt-python.github.io/adapt/ with gallery of examples. Besides, the library presents an high test coverage.

翻译：ADAPT是一个开放源码的网球图书馆,提供若干领域适应方法的实施,该图书馆适合使用“cikit-learn spestator object(应用适当和预测方法的对象)”和“dronorflow”模型,大多数已实施的方法都是以“sestator agnistic”方式开发的,提供了适应多种用途的各种可能性,图书馆提供了与领域适应三大主要战略相对应的三个模块:(一) 基于地物的包含功能转换方法的模块;(二) 采用重新加权技术的范例;(三) 以参数为基础的建议方法,使预先训练的模型适应新的观测,并提议在https://adapt-python.github.io/adapt/上提供完整的文件,并提供各种范例。此外,图书馆还提供高测试覆盖面。