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© SuperDataScienceDeep Learning A-Z
© SuperDataScienceDeep Learning A-Z
© SuperDataScienceDeep Learning A-Z
© SuperDataScienceDeep Learning A-Z
© SuperDataScienceDeep Learning A-Z
© SuperDataScienceDeep Learning A-Z
© SuperDataScienceDeep Learning A-Z
© SuperDataScienceDeep Learning A-Z
Important to know:
• SOMs retain topology of the input set
• SOMs reveal correlations that are not easily identified
• SOMs classify data without supervision
• No target vector -> no backpropagation
• No lateral connections between output nodes
© SuperDataScienceDeep Learning A-Z
Kohonen's Self Organizing Feature
Maps
By Mat Buckland (2004?)
Link:
http://www.ai-junkie.com/ann/som/som1.html
Additional Reading:

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