Using Self Organizing Maps and Nearest-Neighbor to Data Clustering

The data analysis involves the performance of different tasks, which can be performed by many different techniques and strategies. This paper emphasizes the performance of the Data Clustering task using the artificial neural network Self-Organizing Maps as the main artifact. SOM is an Artificial Neural Network based in a competitive unsupervised learning, what implies in the training being entirely guided by the data and the neurons of the map compete among themselves. This neural network has the ability to form mappings that quantify the data, preserving its topology.