loci 0.1.0

Implementation of the LOCI outlier detection algorithm in Python

This is an implementation of the LOCI (local correlation integral) fast outlier detection algorithm in Python, based on the paper:
Papadimitriou, S., Kitagawa, H., Gibbons, P.B. and Faloutsos, C., 2003, March. Loci: Fast outlier detection using the local correlation integral. In Data Engineering, 2003. Proceedings. 19th International Conference on (pp. 315-326). IEEE.

This is an initial first attempt implementation, it is functional (I think) however performance is very limited.

Installation

pip install loci

Dependencies

• Scipy, Numpy
• Python version 3.6 (probably works with 3.x, not tested though)

Example

import numpy as np
import matplotlib.pyplot as plt

from loci.loci import run_loci

data = np.concatenate((np.array([(10, 10), ]), np.random.normal(50, 10, (200, 2))))

loci_res = run_loci(data)
outlier_indices = loci_res.outlier_indices

plt.scatter(data[:, 0], data[:, 1])
plt.scatter(data[outlier_indices, 0], data[outlier_indices, 1], c='r')
plt.show()