Metadata-Version: 2.1
Name: ecf
Version: 0.1
Summary: Empirical Christoffel function for outlier detection
Home-page: https://github.com/PFGimenez/ecf-outlier-detection
Author: Pierre-François Gimenez
Author-email: <pierre-francois.gimenez@laas.fr>
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown

# Empirical Christoffel function for outlier detection

This module is an implementation of the empirical Christoffel function applied to outlier detection as proposed by Lasserre and Pauwels in [The empirical Christoffel function with applications in data analysis](https://arxiv.org/pdf/1701.02886.pdf).

## Example

```python
from ecf import EmpiricalChristoffelFunction
import numpy as np

# Initialize the detector with default degree (4)
c = EmpiricalChristoffelFunction()

# Generate random data points
X = np.array([[0,2],[1,1.5],[0.2,1.9],[100,1.2]])

# Predict the outliers
print(c.fit_predict(X))

# Print the scores
print(c.score_)
```



