Growing multi-experts network with confidence interval estimation

Title:

Growing multi-experts network with confidence interval estimation

Creator:

Kiong, Loo Chu, Rajeswari, Mandava, and Rao, M. V. C.

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:bf5f56f4-a47c-4a6b-8e6b-d9092b5c4f17
uuid:bf5f56f4-a47c-4a6b-8e6b-d9092b5c4f17

Subject:

confidence interval estimation and dynamic structure network

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

A simple and novel method is proposed to estimate the confidence interval of any neural network. A recently introduced Growing Multi-Experts Network (GMN) is embedded with confidence interval estimator whose output directly indicates the defined measure. One-step hybrid learning is employed in which the unsupervised learning method of Growing Neural Gas (GNG) and the supervised learning are implemented simultaneously. Illustrative examples together with the application examples clearly place the utility of the defined measure in sharper focus.

Language:

English

Rights:

http://creativecommons.org/publicdomain/mark/1.0/
policy:public

Source:

Neural network world: international journal on neural and mass-parallel computing and information systems | 2004 Volume:14 | Number:2

Harvested from:

CDK

Metadata only:

false