Self-Organizing Maps: An interesting Neural Network
Introduction Kohonen Map or Self Organizing Maps are based on how our brain cells are organized to form topologically ordered maps that react to different sensory input signals by activating different regions of cerebral cortex. On similar lines, SOM also builds a lattice of neurons with similar neurons being closer to each other and uses this lattice to cluster the data together in lower dimensional space. It is an artificial neural network algorithm developed by Teuvo Kohonen to be applied in the field of unsupervised learning. It is based on the principle of competitive learning where the neurons compete with each other for every input sample with winning neuron making its output as one while rest all make it zero. The process of learning happens in two phases: Ordering Phase where the neurons order themselves topologically and Convergence Phase where the final update of weights happens to move them further closer to the input space. SOM provides an effective and easy w