Python package for Gaussian process regression in python ======================================================== demo_gpr.py explains how to perform basic regression tasks. demo_gpr_robust.py shows how to apply EP for robust Gaussian process regression. gpr.py Basic gp regression package gpr_ep.py GP regression with EP likelihood models covar: covariance functions
Project description
UNKNOWN
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
pygp-1.1.10.tar.gz
(75.2 kB
view details)
Built Distribution
pygp-1.1.10.linux-x86_64.tar.gz
(680.7 kB
view details)
File details
Details for the file pygp-1.1.10.tar.gz.
File metadata
- Download URL: pygp-1.1.10.tar.gz
- Upload date:
- Size: 75.2 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | befa331b952236aa1acba104ed648b1a8cb10a72a951c399a26f44013df0a1bd |
|
| MD5 | b2cc0c705227a7f1f1ca49485fd73272 |
|
| BLAKE2b-256 | 6f91bf1be1c116f7cb79c4140565aa5bbaa9e6c4699bf032d5502d90db2e5dc4 |
File details
Details for the file pygp-1.1.10.linux-x86_64.tar.gz.
File metadata
- Download URL: pygp-1.1.10.linux-x86_64.tar.gz
- Upload date:
- Size: 680.7 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 6aad44888728786dc991124297b9fab5340cbf3609bcafea813326fff50b173e |
|
| MD5 | a04fd19717ee95551026b95b13ad5999 |
|
| BLAKE2b-256 | 3f4b064b791c85534ac363ef2fad95f074b5902a693ad3d2539a2566ccd1cc07 |
