Metodos de Agrupamentos em dois Estagios
This work addresses pattern recognition problems, but it appears incremental as it combines existing clustering algorithms.
The paper tackled pattern recognition by proposing four two-stage clustering methods, with SOINAK achieving the best performance among them.
This work investigates the use of two-stage clustering methods. Four techniques were proposed: SOMK, SOMAK, ASCAK and SOINAK. SOMK is composed of a SOM (Self-Organizing Maps) followed by the K-means algorithm, SOMAK is a combination of SOM followed by the Ant K-means (AK) algorithm, ASCAK is composed by the ASCA (Ant System-based Clustering Algorithm) and AK algorithms, SOINAK is composed by the Self-Organizing Incremental Neural Network (SOINN) and AK. SOINAK presented a better performance among the four proposed techniques when applied to pattern recognition problems.