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/**
* Parallelized variants of LOF.
*
* This parallelization is based on the generalization of outlier detection published in:
*
* Reference:
* <p>
* Erich Schubert, Arthur Zimek, Hans-Peter Kriegel<br />
* Local Outlier Detection Reconsidered: a Generalized View on Locality with
* Applications to Spatial, Video, and Network Outlier Detection<br />
* Data Mining and Knowledge Discovery, 28(1): 190–237, 2014.
* </p>
*/
/*
This file is part of ELKI:
Environment for Developing KDD-Applications Supported by Index-Structures
Copyright (C) 2014
Ludwig-Maximilians-Universität München
Lehr- und Forschungseinheit für Datenbanksysteme
ELKI Development Team
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU Affero General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU Affero General Public License for more details.
You should have received a copy of the GNU Affero General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
@Reference(authors = "E. Schubert, A. Zimek, H.-P. Kriegel", //
title = "Local Outlier Detection Reconsidered: a Generalized View on Locality with Applications to Spatial, Video, and Network Outlier Detection", //
booktitle = "Data Mining and Knowledge Discovery, 28(1): 190–237, 2014.", //
url = "http://dx.doi.org/10.1007/s10618-012-0300-z")
package de.lmu.ifi.dbs.elki.algorithm.outlier.lof.parallel;
import de.lmu.ifi.dbs.elki.utilities.documentation.Reference;
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