@article{id:Siminski2022FuBiNFS,
	abstract = "In data sets some attributes may have higher or lower importance. 
	One of the tools used for data analysis of such datasets are subspace 
	neuro-fuzzy systems. They elaborate fuzzy rules to describe data sets. 
	In subspace neuro-fuzzy systems fuzzy rules exist in subspaces defined with 
	subsets of attributes. In the paper we propose a novel fuzzy biclustering 
	algorithm that groups both objects and attributes in fuzzy clusters. In that 
	way we create a subspace fuzzy rule base for a subspace fuzzy system. The paper 
	is accompanied with numerical examples that show this approach can lead 
	to better generalisation (and thus lower data prediction errors) 
	with preserved interpretation of fuzzy models.",
	author = "Krzysztof Siminski",
	doi = "10.1016/j.fss.2021.07.009",
	issn = "0165-0114",
	journal = "Fuzzy Sets and Systems",
	keywords = "Neuro-fuzzy system; Biclustering; Subspace clustering; Subspace neuro-fuzzy system; Attribute weights",
	pages = "84–106",
	title = "FuBiNFS – fuzzy biclustering neuro-fuzzy system",
	url = "https://www.sciencedirect.com/science/article/pii/S0165011421002499",
	volume = "438",
	year = "2022"
}