What is the method of identifying the most accurately classified data examples using Self Organizing Map?

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The method of identifying the most accurately classified data examples using Self Organizing Map involves the following steps:

1. Train the Self Organizing Map using a dataset of labeled examples.

2. Use the trained SOM to classify a new set of unlabeled examples.

3. Measure the classification accuracy of each example by comparing its assigned class label to its known true label.

4. Calculate a score for each example based on its classification accuracy.

5. Identify the examples with the highest scores, as they are the most accurately classified by the SOM.