Benchmark time series data sets for PyTorch -- the torchtime package

• URL: http://arxiv.org/abs/2207.12503v1
• Date: Mon, 25 Jul 2022 20:06:36 GMT
• Title: Benchmark time series data sets for PyTorch -- the torchtime package
• Authors: Philip Darke, Paolo Missier and Jaume Bacardit
• Abstract summary: The Python package torchtime provides reproducible implementations of commonly used PhysioNet and UEA & UCR time series classification repository data sets for PyTorch. It aims to simplify access to PhysioNet data and enable fair comparisons of models in this exciting area of research.
• Score: 0.12891210250935145
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The development of models for Electronic Health Record data is an area of active research featuring a small number of public benchmark data sets. Researchers typically write custom data processing code but this hinders reproducibility and can introduce errors. The Python package torchtime provides reproducible implementations of commonly used PhysioNet and UEA & UCR time series classification repository data sets for PyTorch. Features are provided for working with irregularly sampled and partially observed time series of unequal length. It aims to simplify access to PhysioNet data and enable fair comparisons of models in this exciting area of research.

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