Presenter : Yu-Ting LU Authors : Ezequiel López -Rubio 2013. TNNLS

Intelligent Database Systems Lab

Presenter : YU-TING LU

Authors : Ezequiel López-Rubio

2013. TNNLS

Improving the Quality of Self-Organizing Maps by Self-Intersection Avoidance

Intelligent Database Systems Lab

OutlinesMotivationObjectivesMethodologyExperimentsConclusionsComments

Intelligent Database Systems Lab

Motivation

• The quality of self-organizing maps is always a

key issue to practitioners.

• This is advantageous as a good quality map

provides a better insight to the structure of the

input data set.

Intelligent Database Systems Lab

Objectives

• Improve the already existing self-organizing models by

decreasing the topology errors of the generated maps.

• Modify the learning algorithm of self-organizing maps

to reduce the number of topology errors.

Intelligent Database Systems Lab

Methodology-basic concepts• Review of Two Self-Organizing Map Models

Intelligent Database Systems Lab

Methodology-basic concepts• Types of Topology Errors

Intelligent Database Systems Lab

Methodology-basic concepts• Self-Intersections

i

j k

r t

s

Intelligent Database Systems Lab

Methodology – self-intersection avoidance

Intelligent Database Systems Lab

Experiments

Intelligent Database Systems Lab

Experiments

Intelligent Database Systems Lab

Experiments

Intelligent Database Systems Lab

Experiments

Intelligent Database Systems Lab

Experiments

Intelligent Database Systems Lab

Experiments

Intelligent Database Systems Lab

Experiments

Intelligent Database Systems Lab

Experiments

Intelligent Database Systems Lab

Experiments

Intelligent Database Systems Lab

Experiments

Intelligent Database Systems Lab

Conclusions

• The maps trained with this approach exhibited less topology errors at the expense of a larger quantization error.

• The procedure can be easily extended to many self-organizing neural networks, and it does not change the structure of the original model.

Intelligent Database Systems Lab

Comments• Advantages

-Improving the Quality of Self-Organizing Maps

• Applications- SOM