Bagging for Biclustering: Application to Microarray Data
Abstract
One of the major tools of transcriptomics is the biclustering that simultaneously constructs a partition of both examples and genes. Several methods have been proposed for microarray data analysis that enables to identify groups of genes with similar expression pro?les only under a subset of examples. We propose to improve the quality of these biclustering methods by adapting the approach of bagging to biclustering problems. The principle consists in generating a set of biclusters and aggregating the results. Our method has been tested with success on artificial and real datasets.
Cite
Text
Hanczar and Nadif. "Bagging for Biclustering: Application to Microarray Data." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2010. doi:10.1007/978-3-642-15880-3_37Markdown
[Hanczar and Nadif. "Bagging for Biclustering: Application to Microarray Data." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2010.](https://mlanthology.org/ecmlpkdd/2010/hanczar2010ecmlpkdd-bagging/) doi:10.1007/978-3-642-15880-3_37BibTeX
@inproceedings{hanczar2010ecmlpkdd-bagging,
title = {{Bagging for Biclustering: Application to Microarray Data}},
author = {Hanczar, Blaise and Nadif, Mohamed},
booktitle = {European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases},
year = {2010},
pages = {490-505},
doi = {10.1007/978-3-642-15880-3_37},
url = {https://mlanthology.org/ecmlpkdd/2010/hanczar2010ecmlpkdd-bagging/}
}