DATABASE FUNDAMENTALS
DATA WAREHOUSING AND DATA MINING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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True
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False
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Either A or B
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None of the above
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Detailed explanation-1: -A self-organizing map (SOM) is a grid of neurons which adapt to the topological shape of a dataset, allowing us to visualize large datasets and identify potential clusters. An SOM learns the shape of a dataset by repeatedly moving its neurons closer to the data points.
Detailed explanation-2: -The reduction in dimensionality that SOMs provide allows people to visualize and interpret what would otherwise be, for all intents and purposes, indecipherable data. SOMs generate subspaces with an unsupervised learning neural network trained with a competitive learning algorithm.
Detailed explanation-3: -It attains this through the learning process-where a sample (a row of your data) is taken from the data, compared for similarity with each of the units on the map. The unit that comes closer in terms of similarity to the sample becomes the winner of that sample.
Detailed explanation-4: -SOM is a machine learning technique that uses dimensionality reduction based on similarities between properties to visualize the relationships between materials in a high-dimensional dataset.