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<h3><a href="#">Table Of Contents</a></h3>
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<li><a class="reference internal" href="#">Welcome to pyFTS’s documentation!</a><ul>
<li><a class="reference internal" href="#what-is-pyfts-library">What is pyFTS Library?</a></li>
<li><a class="reference internal" href="#how-to-reference-pyfts">How to reference pyFTS?</a></li>
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<h1>Welcome to pyFTS’s documentation!<a class="headerlink" href="#welcome-to-pyfts-s-documentation" title="Permalink to this headline">¶</a></h1>
<div class="section" id="what-is-pyfts-library">
<h2>What is pyFTS Library?<a class="headerlink" href="#what-is-pyfts-library" title="Permalink to this headline">¶</a></h2>
<img alt="https://badges.frapsoft.com/os/v2/open-source.png?v=103" src="https://badges.frapsoft.com/os/v2/open-source.png?v=103" />
<img alt="https://img.shields.io/badge/License-GPLv3-blue.svg" src="https://img.shields.io/badge/License-GPLv3-blue.svg" /><img alt="https://img.shields.io/badge/Made%20with-Python-1f425f.svg" src="https://img.shields.io/badge/Made%20with-Python-1f425f.svg" /><p>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 from statistic laymans to experts.</p>
<p>This tool is developed on <a class="reference external" href="http://www.minds.eng.ufmg.br/">MINDS Lab</a>,
headed by Prof. Frederico Gadelha Guimarães from <a class="reference external" href="https://www.ppgee.ufmg.br/">Electrical
Engineering Departament</a> of <a class="reference external" href="https://ufmg.br/">Federal University
of Minas Gerais (UFMG)</a> at Brazil. Also colaborate
with this tool the Brazilian instituitions <a class="reference external" href="http://www.ifnmg.edu.br">Federal Institute of
North of Minas Gerais (IFNMG)</a> and <a class="reference external" href="http://www.ifmg.edu.br">Federal Institute of Minas Gerais
(IFMG)</a> .</p>
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<p class="caption"><span class="caption-text">API Documentation:</span></p>
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<li class="toctree-l1"><a class="reference internal" href="quickstart.html">pyFTS Quick Start</a><ul>
<li class="toctree-l2"><a class="reference internal" href="quickstart.html#how-to-install-pyfts">How to install pyFTS?</a></li>
<li class="toctree-l2"><a class="reference internal" href="quickstart.html#what-are-fuzzy-time-series-fts">What are Fuzzy Time Series (FTS)?</a></li>
<li class="toctree-l2"><a class="reference internal" href="quickstart.html#usage-examples">Usage examples</a></li>
<li class="toctree-l2"><a class="reference internal" href="quickstart.html#references">References</a></li>
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<li class="toctree-l2"><a class="reference internal" href="pyFTS.html">pyFTS package</a><ul>
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<li class="toctree-l3"><a class="reference internal" href="pyFTS.html#module-pyFTS">Module contents</a></li>
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<div class="section" id="how-to-reference-pyfts">
<h2>How to reference pyFTS?<a class="headerlink" href="#how-to-reference-pyfts" title="Permalink to this headline">¶</a></h2>
<a class="reference external image-reference" href="https://doi.org/10.5281/zenodo.1405817"><img alt="https://zenodo.org/badge/DOI/10.5281/zenodo.1405817.svg" src="https://zenodo.org/badge/DOI/10.5281/zenodo.1405817.svg" /></a>
<p>Silva, P. C. L. et al. <em>pyFTS: Fuzzy Time Series for Python (Version v4.0).</em> Belo Horizonte. 2018. DOI: 10.5281/zenodo.1405817. Url: <<a class="reference external" href="https://doi.org/10.5281/zenodo.1405817">https://doi.org/10.5281/zenodo.1405817</a>></p>
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