Skip to main content

Select and score features for causal inferences

Project description

This package has two interfaces:

  1. score_vocab(): Given text (T), vocab (V), outcome(s) Y, and confound(s) (C), this method will score each element of the vocab according to how well it explains each Y, controlling for all of the C’s.

  2. evaluate_vocab(): Measure’s the strength of a vocab’s causal effects on Y (controlling for C).

(c) Reid Pryzant 2019 https://cs.stanford.edu/~rpryzant/ May be used and distributed under the MIT license.

Project details


Download files

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

Source Distribution

causal_selection-1.16.tar.gz (8.9 kB view details)

Uploaded Source

File details

Details for the file causal_selection-1.16.tar.gz.

File metadata

  • Download URL: causal_selection-1.16.tar.gz
  • Upload date:
  • Size: 8.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.4.0 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/3.7.1

File hashes

Hashes for causal_selection-1.16.tar.gz
Algorithm Hash digest
SHA256 242fef6eac3e57cd37a00dcf539367f70c8a27b879af9075febf32d86cb76c05
MD5 e09eb23be9ab0ec75fea5ac64d63b980
BLAKE2b-256 2eee6d87b07e00d433d68aaa21dec5b6d09a30edb31bec354b4d3e750a1160d2

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page