Advances in Feature Selection for Data and Pattern Recognition eBook

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This book presents recent developments and research trends in the field of feature selection for data and pattern recognition, highlighting a number of latest advances. The field of feature selection is evolving constantly, providing numerous new algorithms, new solutions, and new applications. Some of the advances presented focus on theoretical approaches, introducing novel propositions highlighting and discussing properties of objects, and analysing the intricacies of processes and bounds on computational complexity, while others are dedicated to the specific requirements of application domains or the particularities of tasks waiting to be solved or improved. Divided into four parts – nature and representation of data; ranking and exploration of features; image, shape, motion, and audio detection and recognition; decision support systems, it is of great interest to a large section of researchers including students, professors and practitioners.

This is a digital product.

Advances in Feature Selection for Data and Pattern Recognition is written by Urszula Stańczyk and published by Springer. The Digital and eTextbook ISBNs for Advances in Feature Selection for Data and Pattern Recognition are 9783319675886, 3319675885 and the print ISBNs are 9783319675879, 3319675877.