Metadata-Version: 2.1
Name: ml-rapids
Version: 0.0.1.1
Summary: Incremental learning written in C++ exposed in Python
Home-page: https://github.com/JozefStefanInstitute/ml-rapids
Author: Klemen Kenda
Author-email: klemen.kenda@ijs.si
License: GPLv3
Description: # ml-rapids: Incremental learning written in C++ exposed in Python and NodeJS
        
        `ml-rapids` implements incremental learning methods in C++ and exposes them via SWIG in Python and NodeJS.
        
        ## Incremental learning methods:
        
        * Classification
            * Majority Class
            * Naive Bayes
            * Logistic Regression
            * Perceptron
            * VFDT (Very Fast Decision Trees) aka Hoeffding Trees
            * HAT (Hoeffding Adaptive Trees)
            * Bagging
        * Regression
            * /
        
        All the methods implement [`sklearn`](https://scikit-learn.org/) incremantal learner interface (includes `fit`, `partial_fit` and `predict` methods).
        
        
        ## Future plans
        Streaming random forest on top of Hoeffding trees will be implemented.
        
        The library will be exposed via `pypi` and `npm` packages.
        
        Python:
        
        * `pip install ml-rapids`
        
        NodeJS:
        
        * `npm install ml-rapids`
        
        
        ## Development
        Development notes can be read [here](./docs/DEV.md).
        
        ## Acknowledgements
        `ml-rapids` is developed by AILab at Jozef Stefan Institute.
        
        This repository is based strongly on [streamDM-cpp](https://github.com/huawei-noah/streamDM-Cpp).
        
        Project has received funding from European Union's Horizon 2020 Research and Innovation Programme under the Grant Agreement [776115](http://www.perceptivesentinel.eu/) (PerceptiveSentinel).
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Development Status :: 3 - Alpha
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: Operating System :: MacOS
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: Unix
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: >=3.6
Description-Content-Type: text/markdown
