使用 LSTM(python) 在时间序列中进行模式识别 [英] Pattern recognition in time series using LSTM(python)

问题描述

我的应用场景和上一个类似以样本时间序列为例，我希望能够检测此处标记的模式:

但我想用 python 和 LSTM 来做这件事.

我已经阅读了一些关于 RNN 时间序列和词分类的资源.我知道 RNN 如何预测时间序列中的结果，但我很困惑如何在时间序列中找到模式.

我在网上找了很久.但是没有用.请帮助或尝试提供一些如何实现这一目标的想法.

由于我的母语不是英语，如果有什么我没有描述清楚，请追问.谢谢！

解决方案

你可以参考这个不错的教程:https://github.com/guillaume-chevalier/seq2seq-signal-prediction

它可以找到正弦波的模式并生成未来值.

My application scenario is similar to the previous one Pattern recognition in time series

By processing a time series dataset, I Would like to detect patterns that look similar to this: Using a sample time series as an example, I would like to be able to detect the patterns as marked here:

But I want to do it with python and LSTM.

I have read some resouces about the RNN time series and word classification.I know how RNN predicts results in time series, but I'm puzzled how to find a pattern in time series.

I am searching for a long time on net. But no use. Please help or try to give some ideas how to achieve this.

Since I am not a native English speaker, if there is anything I didn't describe clearly, please ask.Thank you!

解决方案

You may refer to this nice tutorial : https://github.com/guillaume-chevalier/seq2seq-signal-prediction

It can find pattern of sinewave and generate future values.

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