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Pattern Recognition

September 25th, 2009

Pattern Recognition

classification : informal – fallacy of distraction

A computational algorithm used to classify raw data (sometimes appropriate action choice is included in the definition).


The term is from machine learning, but has been adapted by cognitive psychologists to describe various theories for how the brain goes from incoming sensory information to action selection.


The various stages of pattern recognition include:

  • Sensor to detect source data (such as the retina for photon reflection)
  • Feature detection in the incoming data (such as border detection, orientation and color)
  • Classification of data based on features (seeing a “tree” or a “keyboard”)
  • Action selection based on classification (jumping out of the way of a moving car coming towards you, not worrying about a moving fly coming towards you)

The pervasiveness of false pattern recognition in human cognition means that it often plays a role in our attempts at reasoning. A large number of informal logical fallacies have been constructed to highlight how this comes out in arguments.

Other Names

Texas Sharpshooter Fallacy

Confirmation bias

Correlation does not equal causation

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Categories: Logic