Ensemble Clustering with Logic Rules
Machine Learning
2012-11-16 v3 Machine Learning
Abstract
In this article, the logic rule ensembles approach to supervised learning is applied to the unsupervised or semi-supervised clustering. Logic rules which were obtained by combining simple conjunctive rules are used to partition the input space and an ensemble of these rules is used to define a similarity matrix. Similarity partitioning is used to partition the data in an hierarchical manner. We have used internal and external measures of cluster validity to evaluate the quality of clusterings or to identify the number of clusters.
Cite
@article{arxiv.1207.3961,
title = {Ensemble Clustering with Logic Rules},
author = {Deniz Akdemir},
journal= {arXiv preprint arXiv:1207.3961},
year = {2012}
}
Comments
Replacing two articles with one