A self-growing cluster development approach to data mining

We describe a data analysis method using a structure adapting neural network with two additional layers. The neural network used is an extended version of a self-organising feature map which can adapt its structure to better represent the clusters in data. Once the clusters are identified, we use tw...

Full description

Saved in:
Bibliographic Details
Main Authors: Alahakoon, D., Halgamuge, S.K., Srinivasan, B.
Format: Conference Proceeding
Language:English
Subjects:
Clustering algorithms
Computer aided manufacturing
Computer science
Data analysis
Data engineering
Data mining
Neural networks
Pattern recognition
Software engineering
Unsupervised learning
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:We describe a data analysis method using a structure adapting neural network with two additional layers. The neural network used is an extended version of a self-organising feature map which can adapt its structure to better represent the clusters in data. Once the clusters are identified, we use two additional layers on the feature map to analyse the clusters and the representation of attributes in the clusters. Simulations and initial results with two simple benchmark data sets are also described.
ISSN:1062-922X
2577-1655
DOI:10.1109/ICSMC.1998.725103