Sparse gaussian process regression
Project description
SGP
Simple gaussian process regression
Installation
pip install sgp
Getting started
from sgp.variational import VariationalGP as VGP
import numpy as np
X_train = np.linspace(0, 5, 1000)
y_train = np.sin(X_train) * X_train
model = VGP().fit(X_train.reshape(-1, 1), y_train)
X_test = np.linspace(0, 10, 100)
y_test, std_test = model.predict(X_test.reshape(-1, 1), return_std=True)
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
sgp-0.3.tar.gz
(296.3 kB
view details)
File details
Details for the file sgp-0.3.tar.gz.
File metadata
- Download URL: sgp-0.3.tar.gz
- Upload date:
- Size: 296.3 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/46.0.0.post20200309 requests-toolbelt/0.9.1 tqdm/4.42.1 CPython/3.7.6
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 8af9b899ecebf9bbf1ec7358b959623b8b3b35e08976647e0e91adf3f39ef489 |
|
| MD5 | 0692d3e1ae7371b35b04d85c8e6685d5 |
|
| BLAKE2b-256 | bafd1c52a87f71e82393db0a0260a63a0d76bd397e4f1be40df7bcf3ddc45b1d |
