rePLS

Name	rePLS JSON
Version	0.0.5 JSON
	download
home_page	None
Summary	Residual Partial Least Squares Learning
upload_time	2024-12-20 17:32:30
maintainer	None
docs_url	None
author	thanhvd
requires_python	None
license	None
keywords	pls repls pcr lr
VCS
bugtrack_url
requirements	No requirements were recorded.
Travis-CI	No Travis.
coveralls test coverage	No coveralls.

            
# rePLS


## Examples 

```python
from rePLS import rePLS, rePCR, reMLR
import numpy as np

n_samples, n_features, n_outcomes, n_confounders = 100, 10,5,2
n_components = 2
rng = np.random.RandomState(0)

Y = rng.randn(n_samples,n_outcomes)
X = rng.randn(n_samples, n_features)
Z = rng.randn(n_samples, n_confounders)

reg = rePLS(Z=Z,n_components=n_components)
reg.fit(X,Y)
Y_pred = reg.predict(X,Z)
```

            

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