Metadata-Version: 2.1
Name: TSFEDL
Version: 1.0.1
Summary: Time Series Spatio-Temporal Feature Extraction using Deep Learning
Home-page: https://github.com/ari-dasci/S-TSFE-DL
Author: Ignacio Aguilera Martos, Ángel Miguel García Vico, Julian Luengo, Francisco Herrera
Author-email: nacheteam@ugr.es
License: UNKNOWN
Description: # TSFEDL: A Python Library for Time Series Spatio-Temporal Feature Extraction and Prediction using Deep Learning.
        
        ## Description
        
        Time series feature extraction is a classical problem in time series analysis. Classical addition and multiplication models have been used for this purpose until the appearance of Artificial Neural Networks and Deep Learning. This problem has gained attention since multiple real life problems imply the usage of time series.
        
        In this repository we introduce a new Python module which compiles 20 backbones for time series feature extraction using Deep Learning. This module has been created to cover the necessity of a versatile and expandable piece of software for practitioners to use in their problems.
        
        ## How to run
        
        First, install dependencies
        
        ```bash
        # clone project
        git clone https://github.com/ari-dasci/S-TSFE-DL.git
        
        # install project
        cd S-TSFE-DL
        pip install -e .
        ```   
        
        In order to run a example, navigate to any file and run it.
        
        ```bash
        cd project/examples
        
        # run example
        python arrythmia_experiment.py
        ```
        
        ## Imports
        This project is setup as a package which means you can now easily import any file into any other file like so:
        
        ```python
        import tensorflow as tf
        import TSFEDL.models_keras as TSFEDL
        
        # get the OhShuLih model
        model = TSFEDL.OhShuLih(input_tensor=input, include_top=True)
        
        # compile and fit as usual
        model.compile(optimizer='Adam')
        model.fit(X, y, epochs=20)
        ```
        
        ## Citation
        
        Please cite this work as:
        
        Time Series Feature Extraction using Deep Learning library (https://github.com/ari-dasci/S-TSFE-DL/)
        
        Paper citation is pending.
        
        <!--
        ```
        @article{YourName,
          title={Your Title},
          author={Your team},
          journal={Location},
          year={Year}
        }
        ```
        -->
        
Keywords: Time series,Feature extraction,Deep learning,recurrent,cnn
Platform: UNKNOWN
Description-Content-Type: text/markdown
