Aliro v0.19

Changelog

• Data visualization improvements including interactive and responsive t-SNE, PCA, feature importance, and learning curve plots for classification tasks
• Add popups to show step-by-step instructions for using Aliro
• Create Aliro Ed intro webpage and production webpage
• Various bugfixes

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See the documentation at https://epistasislab.github.io/Aliro/ for more instructions.

Requirements:

See the installation instructions for prerequisite software requirements.

Installation:

1. Download the production zip Aliro-0_19.zip from the Assets section below (be sure not to download the source code zip).
2. Unzip the archive

Running:

See Using Aliro for instructions.

• From the command line, navigate to the Aliro directory and run the command docker-compose up to start the Aliro server.
• To stop Aliro, kill the process with ctrl+c and wait for the server to shut down.
• Once the webserver is up, connect to http://localhost:5080/ to access the website.

What's Changed

• Add support for running PennAI on Raspberry Pi by @JDRomano2 in #305

• Create aliroed web application with data visualization in D3.js by @HyunjunA in #376

• Add popups to explain how to use aliro and interactive donut chart to show class rate information by @HyunjunA in #380

• Add interactive t-sne, pca, feature important, and learning curve charts to aliro by @HyunjunA in #395

• Update skl_util.py code to deal with exceptional case for learning curve plot by @HyunjunA in #438

• Infvisfrontendmlbackend by @jay-m-dev in #444

New Contributors

• @HyunjunA made their first contribution in #374
• @jay-m-dev made their first contribution in #356
• @JDRomano2 made their first contribution in #305

Full Changelog: v0.17...v0.19