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  1. B Experimental Setups and Acoustic Environments

    In this chapter, the experimental setup and the acoustic environments are described, which are used in this work for illustrating the properties of...
    Chapter
  2. Fast Color Texture-Based Object Detection in Images: Application to License Plate Localization

    The current chapter presents a color texture-based method for object detection in images. A support vector machine (SVM) is used to classify each...
    K.I. Kim, K. Jung, H.J. Kim in Support Vector Machines: Theory and Applications
    Chapter
  3. Application of Support Vector Machines in Inverse Problems in Ocean Color Remote Sensing

    Neural networks are widely used as transfer functions in inverse problems in remote sensing. However, this method still suffers from some problems...
    Chapter
  4. Multiple Model Estimation for Nonlinear Classification

    This chapter describes a new method for nonlinear classification using a collection of several simple (linear) classifiers. The approach is based on...
    Chapter
  5. Active Support Vector Learning with Statistical Queries

    The article describes an active learning strategy to solve the large quadratic programming (QP) problem of support vector machine (SVM) design in...
    P. Mitra, C.A. Murthy, S.K. Pal in Support Vector Machines: Theory and Applications
    Chapter
  6. Using an Adapted Classification Based on Associations Algorithm in an Activity-Based Transportation System

    A lot of research has been carried out in the past by using association rules to build more accurate classifiers. The idea behind these integrated...
    Davy Janssens, Geert Wets, ... Koen Vanhoof in Intelligent Data Mining
    Chapter
  7. Clustering with Intelligent Techniques

    Cluster analysis is a technique for grou** data and finding structures in data. The most common application of clustering methods is to partition a...
    Chapter
  8. Componentwise Least Squares Support Vector Machines

    This chapter describes componentwise Least Squares Support Vector Machines (LS-SVMs) for the estimation of additive models consisting of a sum of...
    K. Pelckmans, I. Goethals, ... B.D. Moor in Support Vector Machines: Theory and Applications
    Chapter
  9. Support Vector Machines for Signal Processing

    This chapter deals with the use of the support vector machine (SVM) algorithm as a possible design method in the signal processing applications. It...
    Chapter
  10. Theoretical and Practical Model Selection Methods for Support Vector Classifiers

    In this chapter, we revise several methods for SVM model selection, deriving from different approaches: some of them build on practical lines of...
    D. Anguita, A. Boni, ... D. Sterpi in Support Vector Machines: Theory and Applications
    Chapter
  11. Adaptive Discriminant and Quasiconformal Kernel Nearest Neighbor Classification

    Nearest neighbor classification assumes locally constant class conditional probabilities. This assumption becomes invalid in high dimensions due to...
    J. Peng, D.R. Heisterkamp, H.K. Dai in Support Vector Machines: Theory and Applications
    Chapter
  12. Simulated Annealing Approach for the Multi-objective Facility Layout Problem

    In general, facility layout problems are occurred if there are changes in requirements of space, people and equipments. When the changes of...
    Umut R. Tuzkaya, Tijen Ertay, Da Ruan in Intelligent Data Mining
    Chapter
  13. Penalty-Reward Analysis with Uninorms: A Study of Customer (Dis)Satisfaction

    In customer (dis)satisfaction research, analytic methods are needed to capture the complex relationship between overall (dis)satisfaction with a...
    Koen Vanhoof, Pieter Pauwels, ... Geert Wets in Intelligent Data Mining
    Chapter
  14. Association Rule Based Specialization in ER Models

    Association rules (ARs) emerged in the domain of market basket analysis and provide a convenient and effective way to identify and represent certain...
    Martine De Cock, Chris Cornelis, ... Etienne E. Kerre in Intelligent Data Mining
    Chapter
  15. Mining Association Rules with Rough Sets

    We say that there is an association between two sets of items when the sets are likely to occur together in transactions. In information retrieval,...
    D.A. Bell, J.W. Guan, D.Y. Liu in Intelligent Data Mining
    Chapter
  16. A User Centred Approach to Management Decision Making

    The management decision making process is becoming increasingly complicated as more detailed and extensive data is available in this information age....
    L.P. Maguire, T.A. McCloskey, ... R. McIvor in Intelligent Data Mining
    Chapter
  17. Techniques to Improve Multi-Agent Systems for Searching and Mining the Web

    Nowadays, an abundant amount of information is created and delivered over electronic media. The information gathering in the Internet is a complex...
    E. Herrera-Viedma, C. Porcel, ... A.G. Lopez-Herrera in Intelligent Data Mining
    Chapter
  18. Gene Regulating Network Discovery

    Gene regulation has been an important research topic for the past 30 years and data processing models based on different assumptions have been...
    Yingjun Cao, Paul P. Wang, Alade Tokuta in Intelligent Data Mining
    Chapter
  19. Semantic Relations and Information Discovery

    The treatment of semantic relations between terms is essential in information retrieval (IR). Each term in a thesaurus might have classes of...
    D. Cai, C.J. van Rijsbergen in Intelligent Data Mining
    Chapter
  20. 5 A Practical Audio Acquisition System Using a Robust GSC (RGSC)

    In the preceding chapter, we have seen that data-dependent beamformers can be efficiently realized in GSC structures. However, GSCs, or more general...
    Chapter
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