Computational Intelligence and Neuroscience / 2011 / Article / Tab 3

Research Article

Multistrategy Self-Organizing Map Learning for Classification Problems

Table 3

Parameter settings for ESOMPSO.

ParameterDataset
IrisXORCancerGlassPendigits

Input vector (Training)12063791497494
Input vector (Testing)302190653498
Input dimension4430916
SOM's Mapping Dimension ( 𝑋 , 𝑌 ) 10 × 1010 × 1010 × 1010 × 1010 × 10
SOM lattice structureStandard
hexagonal
Standard
hexagonal
Standard
hexagonal
Standard
hexagonal
Standard
hexagonal
ESOM lattice structureImproved
Hexagonal
Improved
hexagonal
Improved
hexagonal
Improved
hexagonal
Improved
Hexagonal
Learning rate0.50.50.50.50.5
Number of runs10 times10 times10 times10 times10 times
Epoch10001000100010001000
𝐶 1 2.02.02.02.02.0
𝐶 2 2.02.02.02.02.0
Δ 𝑡 0.10.10.10.10.1
Number of particles100100100100100
PSO problem dimension10 × 1010 × 1010 × 1010 × 1010 × 10
Stop condition (minimum error)0.00001930.00001930.00001930.00001930.0000193

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