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# pyFTS - Fuzzy Time Series for Python
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[![GPLv3 license](https://img.shields.io/badge/License-GPLv3-blue.svg)](http://perso.crans.org/besson/LICENSE.html)
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[![made-with-python](https://img.shields.io/badge/Made%20with-Python-1f425f.svg)](https://www.python.org/)
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[![PyPI pyversions](https://img.shields.io/pypi/pyversions/ansicolortags.svg)](https://pypi.python.org/pypi/pyFTS/)
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[![Open Source Love png2](https://badges.frapsoft.com/os/v2/open-source.png?v=103)](https://github.com/ellerbrock/open-source-badges/)
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## What is pyFTS Library?
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This package is intended for students, researchers, data scientists or whose want to exploit the Fuzzy Time Series methods. These methods provide simple, easy to use, computationally cheap and human-readable models, suitable for statistic laymans to experts.
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@ -53,6 +58,12 @@ Fuzzy Time Series (FTS) are non parametric methods for time series forecasting b
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7. **Data postprocessing**: The inverse operations of step 1.
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## Usage examples
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There is nothing better than good code examples to start. [Then check out the demo Jupyter Notebooks of the implemented method os pyFTS!](https://github.com/petroniocandido/pyFTS/tree/master/pyFTS/notebooks).
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A Google Colab example can also be found [here](https://drive.google.com/file/d/1zRBCHXOawwgmzjEoKBgmvBqkIrKxuaz9/view?usp=sharing).
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## MINDS - Machine Intelligence And Data Science Lab
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This tool is result of collective effort of [MINDS Lab](http://www.minds.eng.ufmg.br/), headed by Prof. Frederico Gadelha Guimarães. Some of research on FTS which was developed under pyFTS:
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