Highly comparative time-series analysis with hctsa
  • Information about hctsa
    • Introduction
    • Getting started
    • Publications using hctsa
    • UMAP Projections
    • Related Time-Series Resources
    • List of included code files
    • FAQ
  • Installing and using hctsa
    • General advice and common pitfalls
    • Installing and setting up
      • Structure of the hctsa framework
      • Overview of an hctsa analysis
      • Compiling binaries
    • Running hctsa computations
      • Input files
      • Performing calculations
      • Inspecting errors
      • Working with hctsa files
    • Analyzing and visualizing results
      • Assigning group labels to data
      • Filtering and normalizing
      • Clustering rows and columns
      • Visualizing the data matrix
      • Plotting the time series
      • Low dimensional representation
      • Finding nearest neighbors
      • Investigating specific operations
      • Exploring classification accuracy
      • Finding informative features
      • Interpreting features
      • Comparing to existing features
      • Working with short time series
    • Working with a mySQL database
      • Setting up the mySQL database
      • The database structure
      • Populating the database with time series and operations
      • Adding time series
      • Retrieving from the database
      • Computing operations and writing back to the database
      • Cycling through computations using runscripts
      • Clearing or removing data
      • Retrieving data from the database
      • Error handling and maintenance
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On this page
  • 🫀ECG Data
  • 🧬 Other Biological Data
  • ⚝ Shapes
  • 🏞️ Image
  • 👋 UWave
  • 🖥️ Simulated
  • 📡 Sensor
  • 💡 Spectrograph

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  1. Information about hctsa

UMAP Projections

Below are some UMAP projections of UEA/UCR time-series classification datasets.

PreviousPublications using hctsaNextRelated Time-Series Resources

Last updated 12 months ago

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In each dataset, each time series is represented in the high-dimensional feature space of hctsa features. In each plot, we show the data projected into a two-dimensional space. Each point in the space is a time series, and we have coloured each point according to its assigned label. In many cases, the unsupervised UMAP projection of the hctsa feature space captures the labeled structure of the data.

Only a selection of the most interesting-looking projections (according to our eyes) are shown here. Oh, did you want to have a play with all the data? It's available on .

Thanks to for doing all the computation shown here!

🫀ECG Data

🧬 Other Biological Data

⚝ Shapes

🏞️ Image

👋 UWave

🖥️ Simulated

📡 Sensor

💡 Spectrograph

Page cover image
UMAP
figshare
Carl Lubba