
488 Large Scale and Big Data
integrated data set (Figure 15.14). The usage of PCA to dene the design of SOM
network selection is unique and completely dynamic. Depending on the data quality
and variance, the size of the selected SOM is dynamically varied. This design made
the SOM training completely adaptable to the dynamic nature of available integrated
data. As the SOM was trained with whole data matrix containing 40 input variables,
SOM had 40 internal weights that were updated iteratively. After a certain number of
iterative training, the weights of the partially trained SOM could be used to visualize
as 2D visual patterns or weight maps. ...