Skip to main content

MLZ: Machine Learning for photo-Z, a photometric redshift PDF estimator

Project description

MLZ is a python code that computes photometric redshift PDFs using machine learning techniques, providing optional extra information.

Author:

Matias Carrasco Kind

Version:

1.1

For a more detailed documentation see: http://lcdm.astro.illinois.edu/static/code/mlz/MLZ-1.1/doc/html/index.html

or go to the doc/ folder and start a web browser opening doc/html/index.html

Any comments, suggestion or question contact me at mcarras2@astro.illinois.edu

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

MLZ-1.1.tar.gz (13.0 MB view details)

Uploaded Source

File details

Details for the file MLZ-1.1.tar.gz.

File metadata

  • Download URL: MLZ-1.1.tar.gz
  • Upload date:
  • Size: 13.0 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for MLZ-1.1.tar.gz
Algorithm Hash digest
SHA256 15373aeb317ab54482b0cf8050d828ebed9e03971dc6bb9c02e23eee68f21e53
MD5 65ce0fbb9a3793d2a687ee8c438cabc7
BLAKE2b-256 450a3700ef3e62ed166eb7cc5d0c7af89770ec96b52db8d7c8cb3f0f43d27dcc

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