Metadata-Version: 2.1
Name: sgp
Version: 0.2.1
Summary: Sparse gaussian process regression
Home-page: https://github.com/marnikitta/sgp
Author: Nikita Marshalkin
Author-email: marnikitta@gmail.com
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown

# SGP

Simple gaussian process regression

## Installation

`pip install sgp`

## Getting started

```python
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)
```




