Skip to main content

A scientific research assistant

Project description

Acton is a modular Python library for active learning. Acton is a suburb in Canberra, where Australian National University is located.

Build Status Documentation Status


Most dependencies will be installed by pip. You will need to manually install:


Install Acton using pip3:

pip install git+

This provides access to a command-line tool acton as well as the acton Python library.

Acton CLI

The command-line interface to Acton is available through the acton command. This takes a dataset of features and labels and simulates an active learning experiment on that dataset.


Acton supports three formats of dataset: ASCII, pandas, and HDF5. ASCII tables can be any file read by, including many common plain-text table formats like CSV. pandas tables are supported if dumped to a file from DataFrame.to_hdf. HDF5 tables are either an HDF5 file with datasets for each feature and a dataset for labels, or an HDF5 file with one multidimensional dataset for features and one dataset for labels.


Acton outputs a file containing predictions for each epoch of the simulation. These are encoded as specified in this notebook.


You will need a dataset. Acton currently supports ASCII tables (anything that can be read by, HDF5 tables, and Pandas tables saved as HDF5. Here’s a simple classification dataset that you can use.

To run Acton to generate a passive learning curve with logistic regression:

acton --data classification.txt --label col20 --feature col10 --feature col11 -o passive.pb --recommender RandomRecommender --predictor LogisticRegression

This command uses columns col10 and col11 as features, and col20 as labels, a logistic regression predictor, and random recommendations. It outputs all predictions for test data points selected randomly from the input data to passive.pb, which can then be used to construct a plot. To output an active learning curve using uncertainty sampling, change RandomRecommender to UncertaintyRecommender.

To show the learning curve, use acton.plot:

python3 -m acton.plot passive.pb

Look at the directory examples for more examples.

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Filename, size & hash SHA256 hash help File type Python version Upload date
acton-0.3.3.tar.gz (21.1 kB) Copy SHA256 hash SHA256 Source None

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN SignalFx SignalFx Supporter DigiCert DigiCert EV certificate StatusPage StatusPage Status page