Paper Info
Title
A New Categorization Numerical Scheme for Mobile Robotic Computing Using Odor Data-set Recognition as a Case.
Abstract
Categorization is one of the most active research and application areas of Data Mining. In this paper, we address the problem of pattern categorization in mobile robotic computing. It is the task of automatically sorting a set of patterns into categories from a predefined set. Most categorization algorithms are sensitive to noise, architecture configuration, Bellman's curse of dimensionality, instability, and complex shapes. Hence, in the present study, a novel numerical scheme (RC) for pattern categorization which provides a good generalization ability with a small empirical error, is described. The experimental study with E-nose of six different MOX gas sensors is presented. Our evaluation method demonstrates the effectiveness and multidisciplinary applications of our approach.
Year
DOI
Venue
2016
10.1016/j.procs.2016.08.031
Procedia Computer Science
Keywords
Field
DocType
Machine Learning,Information Retrieval,Pattern Recognition,Categorization,Features Selection,Support Vector Machines
Data mining,Categorization,Boosting methods for object categorization,Multidisciplinary approach,Computer science,Support vector machine,Curse of dimensionality,Sorting,Artificial intelligence,Machine learning
Conference
Volume
ISSN
Citations 
94
1877-0509
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Choukri Djellali154.48
Mehdi Adda25815.42