Introducing ProsperNN—a Python package for forecasting with neural networks

Introducing ProsperNN—a Python package for forecasting with neural networks

We present the package prosper_nn, that provides four neural network architectures dedicated to time series forecasting, implemented in PyTorch. In addition, prosper_nn contains the first sensitivity analysis suitable for recurrent neural networks (RNN) and a heatmap to visualize forecasting uncerta...

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Bibliographic Details
Main Authors: Nico Beck, Julia Schemm, Claudia Ehrig, Benedikt Sonnleitner, Ursula Neumann, Hans Georg Zimmermann
Format: Article
Language:English
Published: PeerJ Inc. 2024-11-01
Series:PeerJ Computer Science
Subjects:
Price forecasting
Macroeconomic forecasting
Financial forecasting
Software
Recurrent neural networks
Online Access:https://peerj.com/articles/cs-2481.pdf
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