Metadata-Version: 1.1
Name: skpro
Version: 1.0.0b1
Summary: Supervised learning for probabilistic prediction
Home-page: http://skpro.ml
Author: Frithjof Gressmann
Author-email: ucjufgr@ucl.ac.uk
License: BSD
Description-Content-Type: UNKNOWN
Description: ![skpro](/docs/_static/logo/logo.png)
        
        <p align="center">
          <a href="https://travis-ci.org/alan-turing-institute/skpro.svg?branch=master"><img src="https://travis-ci.com/alan-turing-institute/skpro.svg?token=bwQYVkNKkUpai7AxgpfV&branch=master" alt="Build Status"></a>
          <a href="https://opensource.org/licenses/BSD-3-Clause"><img src="https://img.shields.io/badge/License-BSD%203--Clause-blue.svg" alt="License"></a>
        </p>
        
        A supervised domain-agnostic framework that allows for probabilistic modelling, namely the prediction of probability distributions for individual data points.
        
        The package offers a variety of features and specifically allows for
        
        - the implementation of probabilistic prediction strategies in the supervised contexts
        - comparison of frequentist and Bayesian prediction methods
        - strategy optimization through hyperparamter tuning and ensemble methods (e.g. bagging)
        - workflow automation
        
        List of [developers and contributors](AUTHORS.rst)
        
        ### Documentation
        
        The full documentation is [available here](https://alan-turing-institute.github.io/skpro/).
        
        ### Installation
        
        Installation is easy using Python's package manager
        
            $ pip install skpro
        
        ### Contributing
        
        We welcome contributions to the skpro project. Please read our [contribution guide](/CONTRIBUTING.md).
        
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Programming Language :: Python
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Topic :: Software Development :: Libraries
