Skip to main content

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)

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

sgp-0.2.6.tar.gz (292.6 kB view details)

Uploaded Source

File details

Details for the file sgp-0.2.6.tar.gz.

File metadata

  • Download URL: sgp-0.2.6.tar.gz
  • Upload date:
  • Size: 292.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.13.0 pkginfo/1.4.2 requests/2.18.4 setuptools/39.1.0 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/3.6.5

File hashes

Hashes for sgp-0.2.6.tar.gz
Algorithm Hash digest
SHA256 7388e99b8006e61eeb5db92c3e267cf8ce009b11576d65405e2a267788f84309
MD5 b521f5f83b67f1228e679fa1182427f9
BLAKE2b-256 0b332fe738bfd7501e50e88384eb8c7a61b58e7c1a016e8d2a06f8564ed312af

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