Competitive Learning

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What Does Competitive Learning Mean?

Competitive learning is a type of unsupervised learning model used in machine learning and artificial intelligence systems. Some of the interesting new formats of machine learning projects are partially based on competitive learning include self-organizing component neural networks. That makes this an integral idea in the machine learning community.

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Techopedia Explains Competitive Learning

In a competitive learning model, there are hierarchical sets of units in the network with inhibitory and excitatory connections. The excitatory connections are between individual layers and the inhibitory connections are between units in layered clusters. Units in a cluster are either active or inactive.

Scientists explain that the configuration of active units represents an input pattern to be sent to the next level. In processes like vector quantization, professionals can see the principles of competitive learning at work. Competitive learning also exists alongside other learning models such as ensemble learning, where more than one learning unit works together in a dedicated effort toward a result.

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Margaret Rouse
Technology Specialist
Margaret Rouse
Technology Specialist

Margaret is an award-winning writer and educator known for her ability to explain complex technical topics to a non-technical business audience. Over the past twenty years, her IT definitions have been published by Que in an encyclopedia of technology terms and cited in articles in the New York Times, Time Magazine, USA Today, ZDNet, PC Magazine, and Discovery Magazine. She joined Techopedia in 2011. Margaret’s idea of ​​a fun day is to help IT and business professionals to learn to speak each other’s highly specialized languages.