The model is a Conditional Generative Adversarial Network for time series with not regular time intervals.
The model is created to generate a new time series given a training set of them.
The main idea is to use this model to augment the unbalanced dataset of time series, in order to increase the precision of a classifier.
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Requirements:
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python 3
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tensorflow, numpy
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Download the repository
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python3 main.py N M file_in file_times file_out
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N = training set size
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M = time series length
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file_in = file input path
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file_times = file with time stamps of the new time series
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file_out = file output path
If you are interested in this work: https://arxiv.org/abs/1811.08295