Semi-supervised learning with a growing self-organizing map (GSOM) is commonly used to cope with the machine

learning problems. The performance of semi-supervised GSOM is associated with the structure of clustering layer, the activation...

. Semi-supervised learning algorithms may be used as a proper solution in these situations, where E-neighborhood or k nearest neighborhood graphs are employed to build a similarity graph. These graphs, on one hand, have a high degree of sensitivity...

Semi-Supervised Growing Self Organizing Map (SSGSOM) is one of the best methods for online classification with partial labeled data. Many parameters can affect the performance of this method. The structure of GSOM network, ...

of the problems in the real world have numerous data.

Thereforeassigning labels to every data points in these problemsare a cumbersome or even

impossible matter. Semi-supervised learning is one approach to overcome these types of...