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  1. Modular Neural Networks

    We describe in this chapter the basic concepts, theory and algorithms of modular and ensemble neural networks. We will also give particular attention...
    Chapter
  2. Type-1 Fuzzy Logic

    This chapter introduces the basic concepts, notation, and basic operations for the type-1 fuzzy sets that will be needed in the following chapters....
    Chapter
  3. Human Recognition using Face, Fingerprint and Voice

    We describe in this chapter a new approach for human recognition using as information the face, fingerprint, and voice of a person. We have described...
    Chapter
  4. Fingerprint Recognition with Modular Neural Networks and Fuzzy Measures

    We describe in this chapter a new approach for fingerprint recognition using modular neural networks with a fuzzy logic method for response...
    Chapter
  5. Voice Recognition with Neural Networks, Fuzzy Logic and Genetic Algorithms

    We describe in this chapter the use of neural networks, fuzzy logic and genetic algorithms for voice recognition. In particular, we consider the case...
    Chapter
  6. Iterative Single Data Algorithm for Training Kernel Machines from Huge Data Sets: Theory and Performance

    The chapter introduces the latest developments and results of Iterative Single Data Algorithm (ISDA) for solving large-scale support vector machines...
    V. Kecman, T.-M. Huang, M. Vogt in Support Vector Machines: Theory and Applications
    Chapter
  7. Support Vector Machines – An Introduction

    This is a book about learning from empirical data (i.e., examples, samples, measurements, records, patterns or observations) by applying support...
    Chapter
  8. Cancer Diagnosis and Protein Secondary Structure Prediction Using Support Vector Machines

    In this chapter, we use support vector machines (SVMs) to deal with two bioinformatics problems, i.e., cancer diagnosis based on gene expression data...
    Chapter
  9. Sequential Pattern Mining*

    Sequential pattern discovery has emerged as an important research topic in knowledge discovery and data mining with broad applications. Previous...
    Tian-Rui Li, Yang Xu, ... Wu-ming Pan in Intelligent Data Mining
    Chapter
  10. Discovering the Factors Affecting the Location Selection of FDI in China*

    Since the late 1970s, Foreign Direct Investment (FDI) has played an important role in the economic development of China. However, the growth of FDI...
    Li Zhang, Yujie Zhu, ... Guoqing Chen in Intelligent Data Mining
    Chapter
  11. Kernel Discriminant Learning with Application to Face Recognition

    When applied to high-dimensional pattern classification tasks such as face recognition, traditional kernel discriminant analysis methods often suffer...
    J. Lu, K.N. Plataniotis, A.N. Venetsanopoulos in Support Vector Machines: Theory and Applications
    Chapter
  12. Gas Sensing Using Support Vector Machines

    In this chapter we deal with the use of Support Vector Machines in gas sensing. After a brief introduction to the inner workings of multisensor...
    J. Brezmes, E. Llobet, ... J.W. Gardner in Support Vector Machines: Theory and Applications
    Chapter
  13. Tachycardia Discrimination in Implantable Cardioverter Defibrillators Using Support Vector Machines and Bootstrap Resampling

    Accurate automatic discrimination between supraventricular (SV) and ventricular (V) tachycardia (T) in implantable cardioverter defibrillators (ICD)...
    J.L. Rojo-Álvarez, A. García-Alberola, ... Á Arenal-Maíz in Support Vector Machines: Theory and Applications
    Chapter
  14. Improving the Performance of the Support Vector Machine: Two Geometrical Scaling Methods

    In this chapter, we discuss two possible ways of improving the performance of the SVM, using geometric methods. The first adapts the kernel by...
    P. Williams, S. Wu, J. Feng in Support Vector Machines: Theory and Applications
    Chapter
  15. Granular Nested Causal Complexes

    Causal reasoning occupies a central position in human reasoning. In many ways, causality is granular. This is true for: perception, commonsense...
    Lawrence J. Mazlack in Intelligent Data Mining
    Chapter
  16. The Evolution of the Concept of Fuzzy Measure

    Most information discovery processes need to understand the reasons of the success of the inference methods or the usability of the new information,...
    Luis Garmendia in Intelligent Data Mining
    Chapter
  17. Uncertain Knowledge Association Through Information Gain

    The problem of entity association is at the core of information mining techniques. In this work we propose an approach that links the similarity of...
    Athena Tocatlidou, Da Ruan, ... Nikos A. Lorentzos in Intelligent Data Mining
    Chapter
  18. Integrated Clustering Modeling with Backpropagation Neural Network for Effcient Customer Relationship Management

    The rapid progress in digital data acquisition and storage technology has lead to the fast growing tremendous and amount of data stored in databases,...
    Tijen Ertay, Bora Çekyay in Intelligent Data Mining
    Chapter
  19. 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
  20. 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
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