https://github.com/sktime/mlaut
https://github.com/sktime/mlaut
Last synced: 11 months ago
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- Host: GitHub
- URL: https://github.com/sktime/mlaut
- Owner: sktime
- License: other
- Created: 2017-11-28T10:50:28.000Z (over 8 years ago)
- Default Branch: master
- Last Pushed: 2020-04-20T08:58:21.000Z (about 6 years ago)
- Last Synced: 2025-06-30T00:26:43.756Z (12 months ago)
- Language: Python
- Size: 12.6 MB
- Stars: 24
- Watchers: 6
- Forks: 5
- Open Issues: 7
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Metadata Files:
- Readme: README.md
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README
# mlaut (Machine Learning AUtomation Toolbox)
``mlaut`` is a modelling and workflow toolbox in python, written with the aim of simplifying large scale benchmarking of machine learning strategies, e.g., validation, evaluation and comparison with respect to predictive/task-specific performance or runtime. Key features are:
* Automation of the most common workflows for benchmarking modelling strategies on multiple datasets including statistical post-hoc analyses, with user-friendly default settings.
* Unified interface with support for scikit-learn strategies, keras deep neural network architectures, including easy user extensibility to (partially or completely) custom strategies.
* Higher-level meta-data interface for strategies, allowing easy specification of scikit-learn pipelines and keras deep network architectures, with user-friendly (sensible) default configurations.
* Easy setting up and loading of data set collections for local use (e.g., data frames from local memory, UCI repository, openML, Delgado study, PMLB).
* Back-end agnostic, automated local file system management of datasets, fitted models, predictions, and results, with the ability to easily resume crashed benchmark experiments with long running times.
List of [developers and contributors](AUTHORS.rst)
### Documentation
[<<<<<< Documentation available on alan-turing-institute.github.io/mlaut >>>>>>](https://alan-turing-institute.github.io/mlaut)
An example with the basic usage of ``mlaut`` can be found in the following [Jupyter Notebook](https://github.com/alan-turing-institute/mlaut/blob/master/examples/Benchmarking.ipynb)
### Installing
Requires Python 3.6 or greater.
```
pip install mlaut
```