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TSFuse

Python package for automatically constructing features from multi-view time series data.

Installation

TSFuse requires Python 3 and the following packages:

  • Cython>=0.28.5
  • numpy>=1.16.1

These packages can be installed using pip:

pip install "cython>=0.28.5" "numpy>=1.16.1"

To install the latest unreleased version of TSFuse from GitHub:

pip install git+https://github.com/arnedb/tsfuse#egg=tsfuse

Documentation

The documentation is available on https://arnedb.github.io/tsfuse/

Examples on how to use TSFuse are shown in the getting started page and the synthetic sine waves demo notebook.

Paper

To learn more about TSFuse's feature construction method, read the following paper:

Arne De Brabandere, Pieter Robberechts, Tim Op De Beéck and Jesse Davis. Automating Feature Construction for Multi-View Time Series Data. ECML/PKDD Workshop on Automating Data Science 2019.

Metadata

Release files for tsfuse 0.2.3

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for tsfuse 0.2.3
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tsfuse-0.2.3.tar.gz 34.0 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for tsfuse 0.2.3
File Interpreter ABI Platform
tsfuse-0.2.3-cp310-cp310-manylinux_2_39_x86_64.whl CPython 3.10 CPython 3.10 Linux glibc 2.39+ x86-64 Details

Total release size: 77.9 kB

Release files / tsfuse-0.2.3.tar.gz

Download URL tsfuse-0.2.3.tar.gz
Size 34.0 kB
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Release files / tsfuse-0.2.3-cp310-cp310-manylinux_2_39_x86_64.whl

Download URL tsfuse-0.2.3-cp310-cp310-manylinux_2_39_x86_64.whl
Size 44.0 kB
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