Research and development over the past decades have led to significant advances in the field of Pattern Recognition. A textbook covering the basics of attributes and feature selection is the need of the day. The author has made a sincere attempt to meet these requirements.
The various concepts of the subject are arranged logically and explained in a simple reader-friendly language. For a proper under -standing of the subject, a large number of examples with their step-by-step solutions are provided for every concept. Illustrative examples are discussed to emphasize conceptual clarity, thereby presenting typical applications. Highlight extraction, or dimensionality decrease, is a fundamental piece of many AI applications. The need for highlight extraction originates from the source of dimensionality and the high computational expense of controlling high-layered information. In this theory, we center around how to enhance extraction and arrangement of feature extraction. This highly encouraging impact of feature extraction motivated me to look into ways to write the book and create it for attribute selection.
In general, students in Engineering have very limited opportunities to have hands-on access to the operation of Attribute selection and feature extraction. Students typically do not have the opportunity to implement the feature selection in Pattern Recognition and observe real-time performance. This Book approach certainly provides the student with a significant understanding of the design constraints of the Algorithm and their actual performance characteristics. Thus, the concepts developed here are adaptable to other areas of engineering in addition to the biomedical area, such as in Medical Electronics, Machine learning and artificial intelligence courses.
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