Identifying the Components
Abstract
Most, if not all, databases are mixtures of samples from different distributions. In many cases, however, nothing is known about the source components of these mixtures. Therefore, many methods that induce models regard a database as sampled from a single data distribution. Models that do take into account that databases actually are sampled from mixtures of distributions are often superior to those that do not, independent of whether this is modelled explicitly or implicitly.
Cite
Text
van Leeuwen et al. "Identifying the Components." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2009. doi:10.1007/978-3-642-04180-8_17Markdown
[van Leeuwen et al. "Identifying the Components." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2009.](https://mlanthology.org/ecmlpkdd/2009/vanleeuwen2009ecmlpkdd-identifying/) doi:10.1007/978-3-642-04180-8_17BibTeX
@inproceedings{vanleeuwen2009ecmlpkdd-identifying,
title = {{Identifying the Components}},
author = {van Leeuwen, Matthijs and Vreeken, Jilles and Siebes, Arno},
booktitle = {European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases},
year = {2009},
pages = {32},
doi = {10.1007/978-3-642-04180-8_17},
url = {https://mlanthology.org/ecmlpkdd/2009/vanleeuwen2009ecmlpkdd-identifying/}
}