Self-organizing Maps (SOMs)

What is Self-Organizing Map?

• All the entire learning process occurs without supervision.

• Self-Organizing feature map (SOM) refers to a neural network, which is trained using competitive learning. The competition process suggests that, some criteria select a wining processing element. so Self-Organizing feature map is unsupervised neural network.

• Self-Organizing maps are even often referred as Kohonen maps.

• In other words A Self-Organizing map (SOM) or self-organizing feature map (SOFM) is a type of artificial neural network (ANN) that is trained using unsupervised learning to produce a low-dimensional (typically two-dimensional), discretized representation of the input space of the training samples, called a map, and is therefore a method to do dimensionality reduction.

• Self-Organizing maps (SOMs) can be used for clustering of data because Self-Organizing maps are a data visualization technique which reduce the dimensions of data through the use of self-organizing neural networks. It is a type of unsupervised learning. The goal is to discover some underlying structure of the data.

what is Self-Organizing Map algorithm?

• Self-Organizing Map (SOM) is an unsupervised neural network that reduces the input dimensionality in order to represent its distribution as a map.

• They are also known as feature maps, as they are basically retraining the features of the input data, and simply grouping themselves as undirected by the similarity between each other.


How are the output neurons organized in a Self-Organizing map?

• Self-organizing maps have two layers, the first one is the input layer and the second one is the output layer or the feature map.

• unlike other ANN (Artificial Neural network) types, SOM doesn't have activation function in neurons, we directly pass weights to output layer without doing anything.

• Reducing the data dimensions are the main goal of Self-Organizing maps.

Applications of Self-Organizing Maps (SOMs)

• Project prioritization and selection

• Seismic facies analysis for oil and gas exploration

• Failure mode and effects analysis

• creation of artwork

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