Creator:

Simiński, Krzysztof

Contributor:

Korbicz, Józef (1951- ) - red. ; Uciński, Dariusz - red.

Title:

Neuro-rough-fuzzy approach for regression modelling from missing data

Group publication title:

AMCS, Volume 22 (2012)

Subject and Keywords:

neuro-fuzzy ; ANNBFIS ; missing values ; marginalisation ; imputation ; rough fuzzy set ; clustering

Abstract:

Real life data sets often suffer from missing data. The neuro-rough-fuzzy systems proposed hitherto often cannot handle such situations. The paper presents a neuro-fuzzy system for data sets with missing values. The proposed solution is a complete neuro-fuzzy system. The system creates a rough fuzzy model from presented data (both full and with missing values) and is able to elaborate the answer for full and missing data examples. The paper also describes the dedicated clustering algorithm. The paper is accompanied by results of numerical experiments.

Publisher:

Zielona Góra: Uniwersytet Zielonogórski

Date:

2012

Resource Type:

artykuł

DOI:

10.2478/v10006-012-0035-4

Pages:

461-476

Source:

AMCS, Volume 22, Number 2 (2012) ; click here to follow the link

Language:

eng

License CC BY 4.0:

click here to follow the link

Rights:

Biblioteka Uniwersytetu Zielonogórskiego