Lee和Carter去了机器学习:循环神经网络

Computation Theory eJournal Pub Date : 2019-08-22 DOI:10.2139/ssrn.3441030

Ronald Richman, Mario V. Wuthrich

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引用次数: 19

摘要

在本教程中，我们将介绍递归神经网络(RNN)，并描述两种最流行的RNN架构。它们是长短期记忆(LSTM)网络和门控循环单元(GRU)网络。它们的共同应用领域是时间序列建模，我们使用来自瑞士女性和男性人口的数据来演示它们在死亡率预测问题上的应用。

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Lee and Carter go Machine Learning: Recurrent Neural Networks

In this tutorial we introduce recurrent neural networks (RNNs), and we describe the two most popular RNN architectures. These are the long short-term memory (LSTM) network and gated recurrent unit (GRU) network. Their common field of application is time series modeling, and we demonstrate their use on a mortality rate prediction problem using data from the Swiss female and male populations.

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Computation Theory eJournal

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