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
Project details
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
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
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
|