recipe deeplift

DeepLIFT (Deep Learning Important FeaTures)

Homepage

https://github.com/kundajelab/deeplift

Documentation

https://github.com/kundajelab/deeplift/blob/master/README.md

License

OTHER / MIT License

Recipe

/deeplift/meta.yaml

Algorithms for computing importance scores in deep neural networks.

Implements the methods in "Learning Important Features Through Propagating Activation Differences" by Shrikumar, Greenside & Kundaje, as well as other commonly-used methods such as gradients, guided backprop and integrated gradients. See https://github.com/kundajelab/deeplift for documentation and FAQ.

package deeplift

(downloads) docker_deeplift

Versions

0.6.10.0-00.6.9.3-00.6.9.1-00.6.9.0-0

Depends
Required By

Installation

With an activated Bioconda channel (see 2. Set up channels), install with:

conda install deeplift

and update with:

conda update deeplift

or use the docker container:

docker pull quay.io/biocontainers/deeplift:<tag>

(see deeplift/tags for valid values for <tag>)