【工具】时序资料汇总：模型和常见库对比

目录

Part1 领域介绍

推荐教材

推荐公开课

Part2 时序Python库

Part3 相关模型

Time Series Forecasting

Time Series Classification

Anomaly Detection

Time Series Representation

Data Augmentation

Part4 时序数据集

参考

Part1 领域介绍

Time series is a series of data points indexed in time order.

时间序列分析具体包括的任务：

• 检索Indexing (query by content): given a time series and some similarity measure, find the nearest matching time series.

• 聚类Clustering: find groups (clusters) of similar time series.

• 分类Classification: assign a time series to a predefined class.

• 分割Segmentation (Summarization): create an accurate approximation of a time series by reducing its dimensionality while retaining its essential features.

• 预测Forecasting (Prediction): given a time series dataset up to a given time tn, forecast the next values.

• 异常检测Anomaly Detection: find abnormal data points or subsequences.

• 因果分析Rules Discovery: find the rules that may govern associations between sets of time series or subsequences

推荐教材

• Forecasting: Principles and Practice，第三版（英文），第二版（中文）

推荐公开课

• Intel 时间序列分析：讲授时间序列分析，以及用于预测、处理和识别顺序数据的方法。

  • 时间序列和平稳数据简介

  • 数据平滑化、自相关性和自回归积分滑动平均 (ARIMA) 模型等应用

  • 高级时间序列概念，如卡尔曼滤波器 (Kalman Filter) 和傅里叶变换 (Fourier Transformation)

  • 用于时间序列分析的深度学习架构和方法

Part2 时序Python库 ForecastingClasssificationAnomaly DetectionSegmentationTSFeatureProphet✅Kats✅✅✅GluonTS✅✅✅NeuralProphet✅✅✅arch✅AtsPy✅banpei✅cesium✅darts✅PaddleTS✅✅

• Kats，推荐指数：⭐⭐

  • 主页：https://facebookresearch.github.io/Kats/

  • Github：https://github.com/facebookresearch/Kats

• darts，推荐指数：⭐⭐

  • 介绍：a Python library for easy manipulation and forecasting of time series. It contains a variety of models, from classics such as ARIMA to deep neural networks.

  • 主页：https://unit8co.github.io/darts/

  • Github：https://github.com/unit8co/darts

• GluonTS，推荐指数：⭐⭐⭐⭐

  • 主页：https://ts.gluon.ai/index.html

  • Github：https://github.com/awslabs/gluon-ts/

• NeuralProphet，推荐指数：⭐⭐⭐⭐

  • 主页：https://neuralprophet.com/

  • Github：https://github.com/ourownstory/neural_prophet

• arch

  • 介绍：Autoregressive Conditional Heteroskedasticity (ARCH) and other tools for financial econometrics, written in Python.

  • 主页：https://arch.readthedocs.io/en/latest/

  • Github：https://github.com/bashtage/arch

• AtsPy

  • 介绍：Automated Time Series Models in Python

  • Github：https://github.com/firmai/atspy

• banpei

  • 介绍：Anomaly detection library based on singular spectrum transformation

  • Github：https://github.com/tsurubee/banpei

• cesium

  • 介绍：end-to-end machine learning platform for time-series, from calculation of features to model-building to predictions.

  • 主页：https://cesium-ml.org/

  • Github：https://github.com/cesium-ml/cesium

• pyfbad

  • Github：https://github.com/Teknasyon-Teknoloji/pyfbad

更多的模型介绍可以查阅论文[arxiv 2021]A systematic review of Python packages for time series analysis.

Part3 相关模型 Time Series Forecasting ModelUnivariateMultivariateProbabilisticMultiple-series trainingARIMA✅✅VARIMA✅✅AutoARIMA✅ExponentialSmoothing✅✅Theta and FourTheta✅Prophet✅✅FFT (Fast Fourier Transform)✅RegressionModel (incl RandomForest, LinearRegressionModel and LightGBMModel)✅✅✅RNNModel (incl. LSTM and GRU); equivalent to DeepAR in its probabilistic version✅✅✅✅BlockRNNModel (incl. LSTM and GRU)✅✅✅✅NBEATSModel✅✅✅✅TCNModel✅✅✅✅TransformerModel✅✅✅✅TFTModel (Temporal Fusion Transformer)✅✅✅✅Naive Baselines✅ Time Series Classification

• LSTM FCN，LSTM Fully Convolutional Networks for Time Series Classification

Anomaly Detection

• [AAAI 2022] Towards a Rigorous Evaluation of Time-series Anomaly Detection

Time Series Representation

• [AAAI 2022] TS2Vec: Towards Universal Representation of Time Series

Data Augmentation

• [IJCAI 2021] Time Series Data Augmentation for Deep Learning: A Survey

• [arxiv 2020] An empirical survey of data augmentation for time series classification with neural networks

Part4 时序数据集

• UCR Time Series Classification Archive

• UEA & UCR Time Series Classification Repository

参考

时序资料汇总：模型和常见库对比