grant-m-s/AstronomicAL
An interactive dashboard for visualisation, integration and classification of data using Active Learning.
This tool helps scientists and researchers efficiently categorize large datasets, especially when manual labeling is impractical or when data has missing or incorrect labels. You input your raw tabular data, and it helps you interactively visualize, clean, and classify it using active learning. The output is a highly accurate, robust classifier and a reliably labeled dataset, making it ideal for astronomers or anyone working with massive scientific data.
Use this if you need to create accurate classifications from vast, unlabelled, or poorly labeled scientific datasets, especially when classes are imbalanced.
Not ideal if your dataset is small, already perfectly labeled, or if you prefer completely automated classification without human-in-the-loop interaction.
Stars
83
Forks
12
Language
Python
License
GPL-3.0
Category
Last pushed
Mar 04, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/grant-m-s/AstronomicAL"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related frameworks
skyportal/skyportal
Collaborative platform for time-domain astronomy
ritwik12/Celestial-bodies-detection
TensorFlow Image Classifier that can be used to classify whether an image is of a Planet (Earth,...
alessiospuriomancini/cosmopower
Machine Learning - accelerated Bayesian inference
icaromeidem/minas
Machine-learning INtegrated analysis with photometric Astronomical Surveys
ajshajib/dolphin
Automated pipeline for lens modelling based on lenstronomy