mlsanityData to 7 Oct 2026

Feature-based time-series analysis

arXiv 1709.08055 ↗First posted 23 Sep 2017cs.LGcited by 28

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Abstract (arXiv)

This work presents an introduction to feature-based time-series analysis. The time series as a data type is first described, along with an overview of the interdisciplinary time-series analysis literature. I then summarize the range of feature-based representations for time series that have been developed to aid interpretable insights into time-series structure. Particular emphasis is given to emerging research that facilitates wide comparison of feature-based representations that allow us to understand the properties of a time-series dataset that make it suited to a particular feature-based representation or analysis algorithm. The future of time-series analysis is likely to embrace approaches that exploit machine learning methods to partially automate human learning to aid understanding of the complex dynamical patterns in the time series we measure from the world.

Key facts. Cited by 28 papers in the map (data through 7 Oct 2026). First posted on arXiv 23 Sep 2017.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 3; 2022: 6; 2023: 4; 2024: 7; 2025: 4; 2026: 4.

28 papers.

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  1. 2026It's TIME: Towards the Next Generation of Time Series Forecasting Benchmarkscited by 25
  2. 2022A review of machine learning concepts and methods for addressing challenges in probabilistic hydrological post-processing and forecastingcited by 12
  3. 2024TimeMIL: Advancing Multivariate Time Series Classification via a Time-aware Multiple Instance Learningcited by 12
  4. 2022Unifying Pairwise Interactions in Complex Dynamicscited by 8
  5. 2021Novel Features for Time Series Analysis: A Complex Networks Approachcited by 6
  6. 2021An Empirical Evaluation of Time-Series Feature Setscited by 5
  7. 2022Feature-Based Time-Series Analysis in R using the theft Packagecited by 4
  8. 2023Never a Dull Moment: Distributional Properties as a Baseline for Time-Series Classificationcited by 4
  9. 2022Time series features for supporting hydrometeorological explorations and predictions in ungauged locations using large datasetscited by 3
  10. 2022Classification of Stochastic Processes with Topological Data Analysiscited by 3
  11. 2023An ensemble of convolution-based methods for fault detection using vibration signalscited by 3
  12. 2024Survey and Taxonomy: The Role of Data-Centric AI in Transformer-Based Time Series Forecastingcited by 3
16 more
  1. 2025ELATE: Evolutionary Language model for Automated Time-series Engineeringcited by 3
  2. 2025Estimating Time Series Foundation Model Transferability via In-Context Learningcited by 2
  3. 2023Analyzing categorical time series with the R package ctsfeaturescited by 1
  4. 2024Parameter inference from a non-stationary unknown processcited by 1
  5. 2024Learning Global and Local Features of Power Load Series Through Transformer and 2D-CNN: An Image-based Multi-step Forecasting Approach Incorporating Phase Space Reconstructioncited by 1
  6. 2025Interpretable Transformation and Analysis of Timelines through Learning via Surprisabilitycited by 1
  7. 2026FEG-Pro: Forecast-Error Growth Profiling for Finite-Horizon Instability Analysis of Nonlinear Time Seriescited by 1
  8. 2021Hydroclimatic time series features at multiple time scalescited by 0
  9. 2022FRANS: Automatic Feature Extraction for Time Series Forecastingcited by 0
  10. 2023A Dynamic Feedforward Control Strategy for Energy-efficient Building System Operationcited by 0
  11. 2024Path Signatures and Graph Neural Networks for Slow Earthquake Analysis: Better Together?cited by 0
  12. 2024Machine Learning for ALSFRS-R Score Prediction: Making Sense of the Sensor Datacited by 0
  13. 2024SPINEX-TimeSeries: Similarity-based Predictions with Explainable Neighbors Exploration for Time Series and Forecasting Problemscited by 0
  14. 2025An Explainable Neural Radiomic Sequence Model with Spatiotemporal Continuity for Quantifying 4DCT-based Pulmonary Ventilationcited by 0
  15. 2026LLM-Guided ODE Discovery and Parameter Inference from Small-Cohort Aggregate Datacited by 0
  16. 2026Statistical comparisons of time-series feature sets on classification taskscited by 0