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# pyFTS - Fuzzy Time Series for Python
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## pyFTS Library
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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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This project is continously under improvement and contributors are well come.
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## How to reference pyFTS?
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## Fuzzy Time Series (FTS)
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[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.1194859.svg)](https://doi.org/10.5281/zenodo.1194859)
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Silva, P. C. L. et al. *pyFTS: Fuzzy Time Series for Python (Version v4.0).* Belo Horizonte. 2018. DOI: 10.5281/zenodo.1194859. Url: <http://doi.org/10.5281/zenodo.1194859>
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## How to install pyFTS?
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First of all pyFTS was developed and tested with Python 3.6. To install pyFTS using pip tool
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```
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pip install -U pyFTS
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```
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Ou pull directly from the GitHub repo:
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```
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pip install -U git+https://github.com/petroniocandido/pyFTS
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```
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## What are Fuzzy Time Series (FTS)?
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Fuzzy Time Series (FTS) are non parametric methods for time series forecasting based on Fuzzy Theory. The original method was proposed by [1] and improved later by many researchers. The general approach of the FTS methods, based on [2] is listed below:
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1. **Data preprocessing**: Data transformation functions contained at [pyFTS.common.Transformations](https://github.com/petroniocandido/pyFTS/blob/master/pyFTS/common/Transformations.py), like differentiation, Box-Cox, scaling and normalization.
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