Introduction to Pattern Recognition and Data Mining
Pattern recognition is an activity that human beings normally excel in. The task of pattern recognition is encountered in a wide range of human activity. In a broader perspective, the term could cover any context in which some decision or forecast is made on the basis of currently available information. Mathematically, the problem of pattern recognition deals with the construction of a procedure to be applied to a set of inputs; the procedure assigns each new input to one of a set of classes on the basis of observed features. The construction of such a procedure on an input data set is defined as pattern recognition.
A pattern typically comprises some features or essential information specific to a pattern or a class of patterns. Pattern recognition, as per the convention, is the study of how machines can observe the environment, learn to distinguish patterns of interest from their background, and make sound and reasonable decisions about the categories of the patterns. In other words, the discipline of pattern recognition essentially deals with the problem of developing algorithms and methodologies that can enable the computer implementation of many recognition tasks that humans normally perform. The objective is to perform these tasks more accurately, faster, and perhaps more economically than humans and, in many cases, to release them from drudgery resulting from performing routine recognition tasks ...