tsRNN tries to provide a ready-to-use time series forecasting suite for recurrent neural networks. The package is enhanced by basic implementations of traditional statistical algorithms like ARIMA for comparison and provides accuracy measures as well as basic chart options for model comparisons. Note that tsRNN heavily depends on Keras and the TensorFlow Deep Learning framework, both written in Python originally.
Package details |
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Maintainer | |
License | MIT + file LICENSE |
Version | 0.2.2 |
URL | https://github.com/thfuchs/tsRNN |
Package repository | View on GitHub |
Installation |
Install the latest version of this package by entering the following in R:
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