Batch-Learning Self-Organizing Map with Weighted Connections avoiding false-neighbor effects

This study proposes a Batch-Learning Self-Organizing Map with Weighted Connections avoiding false-neighbor effects (BL-WCSOM). We apply BL-WCSOM to several high-dimensional datasets. From results measured in terms of the quantization error, inactive neurons, the topographic error and the computation time, we confirm that BL-WCSOM obtain the effective map reflecting the distribution state of the input data using fewer neurons in less time.