Supervised Hybrid SOM-NG Algorithm
نویسندگان
چکیده
The hybrid SOM-NG algorithm was formulated to improve the quantization precision in Self Organizing Maps by the means of combine both SOM and Neural Gas properties using a parameter γ to tune the topology preservation. A supervised learning algorithm is proposed to take advantage of the balanced hybrid algorithm. The proposed algorithm makes a linear approximation of the goal function for every Voronoi region. The algorithm gives good estimations and well balanced prototype positions combining the benefits of the original algorithms.
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