northanger (northanger) wrote,

pattern recognition

Pattern recognition (also known as classification or pattern classification) is a field within the area of machine learning and can be defined as "the act of taking in raw data and taking an action based on the category of the data" [1]. As such, it is a collection of methods for supervised learning.

Typical applications are automatic speech recognition, classification of text into several categories (e.g. spam/non-spam email messages), the automatic recognition of handwritten postal codes on postal envelopes, or the automatic recognition of images of human faces. The last three examples form the subtopic image analysis of pattern recognition that deals with digital images as input to pattern recognition systems.

Pattern recognition is typically an intermediate step in a longer process. These steps generally are acquisition of the data (image, sound, text, etc.) to be classified, preprocessing to remove noise or normalize the data in some way (image processing, stemming text, etc.), computing features, classification and finally post-processing based upon the recognized class and the confidence level.

Pattern recognition itself is primarily concerned with the classification step. In some cases, such as in neural networks , feature selection and extraction may also be partially or fully automated. {more}


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