Skip to main content

Supervised learning for probabilistic prediction

Project description


<p align="center">
<a href=""><img src="" alt="PyPI version" height="18"></a>
<a href=""><img src="" alt="Build Status"></a>
<a href=""><img src="" alt="License"></a>

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](

### Installation

Installation is easy using Python's package manager

$ pip install skpro

### Contributing & Citation

We welcome contributions to the skpro project. Please read our [contribution guide](/

If you use skpro in a scientific publication, we would appreciate [citations](CITATION.rst).

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for skpro, version 1.0.1
Filename, size File type Python version Upload date Hashes
Filename, size skpro-1.0.1.tar.gz (458.8 kB) File type Source Python version None Upload date Hashes View

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Huawei Huawei PSF Sponsor Microsoft Microsoft PSF Sponsor NVIDIA NVIDIA PSF Sponsor Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page