简体繁体 English

我可以对年度数据执行多元时间序列预测吗

[英]Can I perform multivariate time series forecasting on yearly data

原文 2022-01-30 10:22:32 7 1 python/ machine-learning/ deep-learning/ time-series/ lstm

I wanted to build an LSTM model that can work on a yearly dataset.我想构建一个可以处理年度数据集的 LSTM model。 I found that most of the articles or resources about LSTM use DateTime instead of the year, but my dataset only has year and cannot drill down to month-day...我发现大多数关于 LSTM 的文章或资源都使用 DateTime 而不是年份，但我的数据集只有年份，不能深入到月日......

Is LSTM able to work on a small yearly dataset? LSTM 是否能够处理小型的年度数据集？ Or there is any model more suitable for the task?或者有没有更适合这个任务的model？

1 个解决方案

The Heisenberg uncertainty principle states that:海森堡测不准原理指出：

a given function cannot be arbitrarily compact both in time and frequency, defining an “uncertainty” lower bound.给定的 function 在时间和频率上都不能任意紧凑，从而定义了“不确定性”下限。

Or with other words, if you want to forecast patterns on a daily basis, you need at least data on a daily basis, if you want data on monthly basis you need data on monthly basis if you indeed want to predict a yearly forecast, then you can use your yearly data but you will not be able to drill further down.或者换句话说，如果你想每天预测模式，你至少需要每天的数据，如果你想要每月的数据，你需要每月的数据，如果你确实想预测年度预测，那么您可以使用您的年度数据，但您将无法进一步向下钻取。

使用多元时间序列预测的需求预测 - Demand Forecasting using multivariate time Series forecasting

在 Keras 中使用 LSTM 进行多元时间序列预测（关于未来数据） - Multivariate time series forecasting with LSTMs in Keras (on future data)

使用 LSTM 将单变量转换为多变量时间序列预测 - Transform Univariate to Multivariate Time Series Forecasting with LSTM

具有 3 个月数据集的多元时间序列预测 - Multivariate time series forecasting with 3 months dataset

Keras多元时间序列预测模型返回NaN作为MAE和损失 - Keras multivariate time series forecasting model returns NaN as MAE and loss

多元数据序列的多元时间序列分析 - Multivariate Time Series Analysis on multiple data series

如何在Python中预处理时间序列数据以进行预测 - How to preprocess time series data in Python for forecasting

具有不规则数据的 python 中的时间序列预测 - Time series forecasting in python with irregular data

用PyBrain神经网络预测时间序列数据 - Forecasting time series data with PyBrain Neural Networks

如何重塑为 Keras 用于 XGBoost 的多步和多变量时间序列预测创建的 3D 张量？ - How to reshape a 3D tensor created for multistep and multivariate time series forecasting for Keras to be used in XGBoost?

暂无

暂无

声明:本站的技术帖子网页，遵循CC BY-SA 4.0协议，如果您需要转载，请注明本站网址或者原文地址。任何问题请咨询:yoyou2525@163.com.

相关问题 使用多元时间序列预测的需求预测 - Demand Forecasting using multivariate time Series forecasting 在 Keras 中使用 LSTM 进行多元时间序列预测（关于未来数据） - Multivariate time series forecasting with LSTMs in Keras (on future data) 使用 LSTM 将单变量转换为多变量时间序列预测 - Transform Univariate to Multivariate Time Series Forecasting with LSTM 具有 3 个月数据集的多元时间序列预测 - Multivariate time series forecasting with 3 months dataset Keras多元时间序列预测模型返回NaN作为MAE和损失 - Keras multivariate time series forecasting model returns NaN as MAE and loss 多元数据序列的多元时间序列分析 - Multivariate Time Series Analysis on multiple data series 如何在Python中预处理时间序列数据以进行预测 - How to preprocess time series data in Python for forecasting 具有不规则数据的 python 中的时间序列预测 - Time series forecasting in python with irregular data 用PyBrain神经网络预测时间序列数据 - Forecasting time series data with PyBrain Neural Networks 如何重塑为 Keras 用于 XGBoost 的多步和多变量时间序列预测创建的 3D 张量？ - How to reshape a 3D tensor created for multistep and multivariate time series forecasting for Keras to be used in XGBoost?

相关标签

粤ICP备18138465号 © 2020-2024 STACKOOM.COM