时序资料汇总:模型和常见库对比

Datawhale

共 3524字,需浏览 8分钟

 · 2022-08-26

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 DetectionSegmentationTSFeature
Prophet



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 training
ARIMA

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
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