What is the method for determining the nearest class example (observation) to a class in Self Organizing Map?

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The method for determining the nearest class example (observation) to a class in Self Organizing Map is by calculating the Euclidean distance between each class in the SOM and the given observation or data point. The class with the shortest distance is considered as the nearest or best matching unit (BMU) and is used to classify the new observation. The distance is calculated using the formula:

distance = √(Σ(xi-yi)2)

where xi is the value of the i-th feature in the observation, yi is the value of the i-th feature in the SOM class, and Σ denotes summation over all features.

Once the BMU is found, the observation is assigned to that class or cluster. This method, also known as the winner-takes-all approach, is commonly used in SOM for unsupervised classification and clustering of data.